# Sunspots and Sea Surface Temperature

Guest Post by Willis Eschenbach

I thought I was done with sunspots … but as the well-known climate scientist Michael Corleone once remarked, “Just when I thought I was out … they pull me back in”.  In this case Marcel Crok, the well-known Dutch climate writer, asked me if I’d seen the paper from Nir Shaviv called “Using the Oceans as a Calorimeter to Quantify the Solar Radiative Forcing”, available here. Dr. Shaviv’s paper claims that both the ocean heat content and the ocean sea surface temperature (SST) vary in step with the ~11 year solar cycle. Although it’s not clear what “we” means when he uses it, he says: “We find that the total radiative forcing associated with solar cycles variations is about 5 to 7 times larger than just those associated with the TSI variations, thus implying the necessary existence of an amplification mechanism, though without pointing to which one.” Since the ocean heat content data is both spotty and incomplete, I looked to see if the much more extensive SST data actually showed signs of the claimed solar-related variation.

Before deriving the global heat flux from the observed ocean heat content, it is worth while to study in more detail the different data sets we used, and in particular, to better understand their limitations. Since we wish to compare them to each other, we begin by creating comparable data sets, with the same resolution and time range. Thus, we down sample higher resolution data into one year bins and truncate all data sets to the range of 1955 to 2003.

I assume the 1955 start of their data is because the ocean heat content data starts in 1955. Their study uses the HadISST dataset, the “Ice and Sea Surface Temperature” data, so I went to the marvelous KNMI site and got that data to compare to the sunspot data. Here are the untruncated versions of the SIDC sunspot and the HadISST sea surface temperature data.

Figure 1. Sunspot numbers (upper panel) and sea surface temperatures (lower panel).

So … is there a solar component to the SST data? Well, looking at Figure 1, for starters we can say that if there is a solar component to SST, it’s pretty small. How small? Well, for that we need the math. I often start with a cross-correlation. A cross-correlation looks not only at how well correlated two datasets might be. It also shows how well correlated the two datasets are with a lag between the two. Figure 2 shows the cross-correlation between the sunspots and the SST:

Figure 2. Cross-correlation, sunspots and sea surface temperatures. Note that they are not significant at any lag, and that’s without accounting for autocorrelation.

So … I’m not seeing anything significant in the cross-correlation over full overlap of the two datasets, which is the period 1870-2013. However, they haven’t used the full dataset, only the part from 1955 to 2003. That’s only 49 years … and right then I start getting nervous. Remember, we’re looking for an 11-year cycle. So results from that particular half-century of data only represent three complete solar cycles, and that’s skinny … but in any case, here’s cross-correlation on the truncated datasets 1955-2003:

Figure 3. Cross-correlation, truncated sunspots and sea surface temperatures 1955-2003. Note that while they are larger than for the full dataset, they are still not significant at any lag, and that’s without accounting for autocorrelation.

Well, I can see how if all you looked at was the shortened datasets you might believe that there is a correlation between SST and sunspots. Figure 3 at least shows a positive correlation with no lag, one which is almost statistically significant if you ignore autocorrelation.

But remember, in the cross-correlation of the complete dataset shown back in Figure 2, the no-lag correlation is … well … zero. The apparent correlation shown in the half-century dataset disappears entirely when we look at the full 140-year dataset.

This highlights a huge recurring problem with analyzing natural datasets and looking for regular cycles. Regular cycles which are apparently real appear, last for a half century or even a century, and then disappear for a century …

Now, in Shaviv2008, the author suggests a way around this conundrum, viz:

Another way of visualizing the results, is to fold the data over the 11-year solar cycle and average. This reduces the relative contribution of sources uncorrelated with the solar activity as they will tend to average out (whether they are real or noise).

In support of this claim, he shows the following figure:

Figure 4. This shows Figure 5 from the Shaviv2008 paper. Of interest to this post is the top panel, showing the ostensible variation in the averaged cycles.

Now, I’ve used this technique myself. However, if I were to do it, I wouldn’t do it the way he has. He has aligned the solar minimum at time t=0, and then averaged the data for the 11 years after that. If I were doing it, I think I’d align them at the peak, and then take the averages for say six years on either side of the peak.

But in any case, rather than do it my way, I figured I’d see if I could emulate his results. Unfortunately, I ran into some issues right away when I started to do the actual calculations. Here’s the first issue:

Figure 5. The data used in Shaviv2008 to show the putative sunspot-SST relationship.

I’m sure you can see the problem. Because the dataset is so short (n = 49 years), there are only four solar minima—1964, 1976, 1986, and 1996. And since the truncated data ends in 2003, that means that we only have three complete solar cycles during the period.

This leads directly to a second problem, which is the size of the uncertainty of the results of the “folded” data. With only three full cycles to analyze, the uncertainty gets quite large. Here are the three folded datasets, along with the mean and the 95% confidence interval on the mean.

Figure 6. Sea surface temperatures from three full solar cycles, “folded” over the 11-year solar cycle as described in Shaviv2008

Now, when I’m looking for a repetitive cycle, I look at the 95% confidence interval of the mean. If the 95%CI includes the zero line, it means the variation is not significant. The problem in Figure 6, of course, is the fact that there are only three cycles in the dataset. As a result, the 95%CI goes “from the floor to the ceiling”, as the saying goes, and the results are not significant in the slightest.

So why does the Shaviv2008 result shown in Figure 4 look so convincing? Well … it’s because he’s only showing one standard error as the uncertainty in his results, when what is relevant is the 95%CI. If he showed the 95%CI, it would be obvious that the results are not significant.

However, none of that matters. Why not? Well, because the claimed effect disappears when we use the full SST and sunspot datasets. Their common period goes from 1870 through 2013, so there are many more cycles to average. Figure 7 shows the same type of “folded” analysis, except this time for the full period 1870-2013:

Figure 7. Sea surface temperatures from all solar cycles from 1870-2013, “folded” over the 11-year solar cycle as described in Shaviv2008

Here, we see the same thing that was revealed by the cross-correlation. The apparent cycle that seemed to be present in the most recent half-century of the data, the apparent cycle that is shown in Shaviv2008, that cycle disappears entirely when we look at the full dataset. And despite having a much narrower 95%CI because we have more data, once again there is no statistically significant departure from zero. At no time do we see anything unexplainable or unusual at all

And so once again, I find that the claims of a connection between the sun and climate evaporate when they are examined closely.

Let me be clear about what I am saying and not saying here. I am NOT saying that the sun doesn’t affect the climate.

What I am saying is that I still haven’t found any convincing sign of the ~11-year sunspot cycle in any climate dataset, nor has anyone pointed out such a dataset. And without that, it’s very hard to believe that even smaller secular variations in solar strength can have a significant effect on the climate.

So, for what I hope will be the final time, let me put out the challenge once again. Where is the climate dataset that shows the ~11-year sunspot/magnetism/cosmic rays/solar wind cycle? Shaviv echoes many others when he claims that there is some unknown amplification mechanism that makes the effects “about 5 to 7 times larger than just those associated with the TSI variations” … however, I’m not seeing it. So where can we find this mystery ~11-year cycle?

Please use whatever kind of analysis you prefer to demonstrate the putative 11-year cycle—”folded” analysis as above, cross-correlation, wavelet analysis, whatever.

Regards,

w.

My Usual Request: If you disagree with someone, myself included, please QUOTE THE EXACT WORDS YOU DISAGREE WITH. This prevents many flavors of misunderstanding, and lets us all see just what it is that you think is incorrect.

Subject: This post is about the quest for the 11-year solar cycle. It is not about your pet theory about 19.8 year Jupiter/Saturn synoptic cycles. If you wish to write about them, this is not the place. Take it to Tallbloke’s Talkshop, they enjoy discussing those kinds of cycles. Here, I’m looking for the 11-year sunspot cycles in weather data, so let me ask you kindly to restrict your comments to subjects involving those cycles.

Data and Code: I’ve put the sunspot and HadISST annual data online, along with the R computer code, in a single zipped folder called “Shaviv Folder.zip

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norah4you
June 6, 2014 11:16 pm

Mother Nature isn’t a joke nor is she easy to comprehend and understand 🙂

Santa Baby
June 6, 2014 11:21 pm

UV is also hot?

June 6, 2014 11:40 pm

Willis says
Where is the climate dataset that shows the ~11-year sunspot/magnetism/cosmic rays/solar wind cycle? Shaviv echoes many others when he claims that there is some unknown amplification mechanism that makes the effects “about 5 to 7 times larger than just those associated with the TSI variations” … however, I’m not seeing it. So where can we find this mystery ~11-year cycle?
henry says
it is very simple really. you must just look at the right parameters. As stated before, I would not look at SSN for various reasons. I am not going to argue that again.
Here are my latest results for the drop in maximum temperatures
change/decrease in maximum temperatures (henry’s global average, 27 stations NH and 27 station SH)
last 40 years (from 1974) +0.034 degree C/yr
last 34 years (from 1980) +0.026 degree C/ yr
last 24 years (from 1990) +0.014 degree C/yr
Here is a graph showing the drop in the magnetic fields from the sun
clearly you can draw a binomial from top and bottom, as a best fit for the general drop in field strength, coming to a lowest point soon? Clearly you can see a binomial for the drop in maximum temperatures?
There must be a correlation between the drop in energy coming in (maxima) and drop in field strength.
(my proposed mechanism) The mechanism is that lower field strengths on the sun allow somewhat more of the most energetic particles to escape from the sun, hence the noted increase in ozone and others TOA. In turn, more ozone and others deflect more sunlight to outer space due to absorbance and re-radiation. Hence we are cooling, globally.

June 6, 2014 11:51 pm

Looking for evidence of solar influence on climate in 11 year cycles is a dead end. Solar variation can only have caused about 0.8C in 150 years. Claiming that because 11 year cycles cannot be seen in noisy incomplete data so solar variation has little influence is also a dead end.
The mechanism for solar influence is simple. The UV frequencies that vary most greatly between cycles are the frequencies that penetrate below the diurnal overturning layer of the oceans, allowing energy to accumulate. This process is slow and cumulative. The apparent absence of clear 11 year cycles in ocean temps in no way shape or form disproves solar variation driving climate changes observed over 150 years.
In contrast, AGW due to CO2 is easily disproved. Empirical experiment shows the oceans are not warmed by DWLWIR. Empirical experiment also shows that the oceans respond as a selective surface to incoming solar radiation not as a “near blackbody” as per the crazed claims of climastrologists. Further, the effective emissivity (not the apparent emissivity) of water is below 0.8. The oceans need the atmosphere to cool and the atmosphere in turn needs radiative gases to cool. Global warming due to CO2 is physically impossible.
That only leaves two options for 0.8C in 150 years. Internal variability or solar variability. Solar variability is prime suspect. All you need to understand is that water is not a “near blackbody” or even close.

Frederick Michael
June 6, 2014 11:55 pm

Shouldn’t the sunspots (or whatever the real solar driver is) drive the FIRST DERIVATIVE of temperature, not simply the temperature? If so, then the earth’s temperature might have a slow impulse response which could be much longer than 11 years. The result could easily act like a low-pass filter — and you wouldn’t see much happening within the 11 year periodicity of the sunspot cycles. BUT, give us have a few weak cycles in a row and the accumulated effect would be significant.
Given the radiative heat loss that results from higher temperatures, a good model (of global temp as a function of sunspots) might be some kind of exponential smoothing. That would be true even if global temp responded quickly enough to “follow” the 11 year solar cycle, but I’m thinking that the right smoothing constant would be too small for that.
Another way to think of this is as a low-pass RC circuit. The input is a current source which varies over time (but is not AC; it’s always >0). The circuit is a capacitor to ground (representing the thermal inertial of the earth) and a resistor to ground (representing the radiative loss as a function of temperature.) Over a small temperature range, we can model the radiative loss as proportional to temperature and ignore the higher order effects.
Either way, it’d be interesting to see if you can get a better fit, showing temperature rising after strong solar cycles and falling after weaker ones. Unfortunately, the El Nino/La Nina cycles add a hell of a lot of noise to the data.

RACookPE1978
Editor
June 7, 2014 12:05 am

OK.
So, let’s play the ‘maybe sunspots-co-relate-to-something-else-in-the-sun-that-might-affect-global temperatures on earth over long periods of time game. It does make sense somehow, but we may not (actually really and absolutely do not know what) that relationship might be.
Look again above at the plots.
Look not a 11 year cycle, but a six-sunspot 11 year (33 positive/33 year negative) 66 year cycle of alternating “positive” and “negative” cycles that themselves are near-equal, but over a three set cycle may mean something important .

phlogiston
June 7, 2014 12:20 am

These studies by Willis aimed at reproducing important (apparently) research findings are of enormous scientific value. The issue of research repeatability has been highlighted recently in this Nature editorial concerning preclinical cancer research:
http://www.nature.com/nature/journal/v483/n7391/full/483531a.html
In short, the pharmaceutical company Amgen in California tried to repeat 53 “landmark” cancer genetic studies and was able to do so in only 6 cases. The German company Bayer tried the same thing with a different (partly overlapping) set of studies and could reproduce only 25% of them.
This shocking result is prompting a change in research and publication practice with more encouragement of attemps to repeat published research. While not as glamourous as blazing a trail with an (apparently) original finding, it does a service to science of great value.

June 7, 2014 12:38 am

RACookPE1978
http://wattsupwiththat.com/2014/06/06/sunspots-and-sea-surface-temperature/#comment-1656249
Look again above at the plots.
Henry says
No\!
Look at this one
Hale cycle (the “plus” + the “minus” ) is from 1970-1990 and the next is from 1990-2013.
However, fleld strengths are so low that it must come to a dead end stop, probably reversing. My bet is on 2015 or 2016. For the next 44 years (from 2015 or 2016) field strengths will be the mirror of previous 44 years, unless somebody knows better?

richard verney
June 7, 2014 12:49 am

June 6, 2014 at 11:51 pm
////////////////////////////////////////////////////
We hold similar views, and recall that we engaged in much discussion on this on Willis’ article on ‘Radiating the Oceans’ (which i personally consider to be not one of Willis’ stronger articles – sorry willis, just my personal opinion). However, the point that the warmists would raise is that if DWLWIR heats the atmosphere, even if it does not heat the ocean below, then due to the warmer atmosphere above the ocean,the heat loss from the ocean is lower/slower, thereby helping to maintain or even produce higher ocean temperatures over time.
In another Willis’ article (I can’t rember which one), I pointed out that if one considers the optical absorption characteristics of LWIR in water, if DWLWIR is of the level claimed by K&T (in their energy budget cartoon), and if that energy is absorbed by the oceans in accordance with accepted LWIR absorption charactericis in water, there would be so much energy absorbed in the first few micron layer that this potentially would produce about 14 to 18 metres of rainful annually. I suggested that since we are not observing such levels of annual rainfall, it suggests that DWLWIR is not of the level claimed, or it lacks sensible energy, or it is simply not (for some other reason) being absorbed by the oceans.
Indeed, I am sceptical as to whether all the DWLWIR can even reach the oceans. The average wind conditions over the oceans s BF 4 to 5. in these wind conditions, there is already quite a lot of wind swept spray and spume. Spray and spume is, of course, a fine mist of water droplets, and these droplets are more than a few microns in size and therefore would be capable of absorbing about 60% of all DWLWIR before it even reaches the ocean below.
Now I am not suggesting that there is a homogenous layer of windswept spray and spume which universally covers all the oceans all of the time. But what one has to rememeber is that globally, as you read this there are large areas of the oceans which are subject to BF 7 to 8 and above. Indeed, there will be areas of the ocean where large storms are raging with BF10 conditions. We have all seen the size of huricanes and cyclones, and one can imagine the area and sea state involved. Where these storms are raging, the spray and spume which is a layer of water droplets completely divorced from the ocean below, acts much like sun cream (or a sun parasol), but blocking DWLWIR from impacting the ocean below. So it would appear that a not insignificant proportion of the DWLWIR in the K&T energy budget cartoon, does not, or cannot reach the ocean below.
The divorced layer of spray and spume in these conditions would almost fully absorb DWLWIR and as it does so, it would heat and would be carried upwards in the atmosphere initally warming the atmosphere and keeping the DWLWIR away from the ocean below.
I have yet to see a wholly convincing argument as to why if DWLWIR is of the order suggested by K&T (in their energy budget cartoon), and if DWLWIR is absorpbed by the oceans in accordance with accepted LWIR absorption charateristics in water, there is not a very substantial amount of rainfall (much more than we observe annually) and/or that this would not lead to copious amounts of evaporation.
When considering this, one has to bear in mind that the heat flux is upwards in the first few millimetres of the ocean such that energy absorbed in the first few microns cannot find its way downwards by conduction, and ocean over turning is a slow mechanical process such that even if the top few microns of the ocean are over turned, the rate of overturning would be slower than the speed at which energy is absorption in the first few micron layer 9such that the ocean over turning process does not disipate energy downwards at a quick enough rate to stop the rapid evaporation that one would expect to see at the top of the ocean give the amount and rate of absorption of DWLWIR in the first 3 or 4 microns of the ocean).

RACookPE1978
Editor
June 7, 2014 12:58 am

HenryP says:
June 7, 2014 at 12:38 am (replying to) RACookPE1978

Henry says
No\!
Look at this one
Hale cycle (the “plus” + the “minus” ) is from 1970-1990 and the next is from 1990-2013.

Oh, I can – And will!! – agree with you about the coming slower sunspot/solar cycle-magnetic field total questions.
But!!!! I do NOT know what will happen due to that change.
So, to cover for that lack of knowledge, I would prefer to focus on the earlier longer-term 66 year patterns of “several high, several low” cycles we see since 1650 as the earth warms from the LIA. Do those cycles matter?

Peter Hartley
June 7, 2014 1:00 am

A problem with using a long time series of SST is that early measures are not comparable to more recent ones. There has been a long debate about adjustments for different buckets used to measure sea water temperatures, buckets versus engine intake, and the changing coverage of the oceans because temperatures were only measured where ships went in the pre-satellite/ARGO days. I seem to recall that both John Daly and Steve McIntyre have discussed these measurement issues.

June 7, 2014 1:02 am

Solar variability is prime suspect.
Henry says
according to AGW theory (warming caused by more CO2) minimum temperatures should show a rise. Namely, it is alleged that increased GHG causes a delay in cooling.
Consequently, minimum temps. should be rising.
Here are my latest results for the change in the speed of minimum temperatures (27 weather stations NH + 27 weather stations NH, balanced to zero latitude and 70/30 @sea/inland)
last 40 years (from 1974) +0.004 degree C/yr
last 34 years (from 1980) +0.007 degree C/ yr
last 24 years (from 1990) +0.004 degree C/yr
last 14 years (from 2000) -0.009 degree/yr
Now, note that the observed values are very low, indeed, yet it seems they are significant.
Namely, setting the periods out against the speed of warming/cooling I get a binomial again with rsquared eual to 1 (100% correlation)
There is no error in the equation…..
Hence, there is no AGW There is no room for it in my equation.
unless AGW behaves naturally?
ergo
Temperature depends on solar variability only.
Have a good weekend.

June 7, 2014 1:04 am

Willis, I did find a graph from NASA used for teachers which discusses sunspots at:
http://image.gsfc.nasa.gov/poetry/activity/s2.pdf
At least one can say that the correlation is weak. But another more recent work by Zhou and Tung shows a correlation:
http://depts.washington.edu/amath/old_website/research/articles/Tung/journals/2010JCLI3232.pdf
Another article I have read was that the SST in the (sub)tropics rapidely increases with 0.3-0.5 K and back over a cycle, but I lost the link.
I am agnostic on that point (solar cycle influence on SST), but there is definitely a response of weather patterns on the solar cycle via the UV-route: UV increases about 10% during solar maxima, which alters O3 abundance in the tropical lower stratosphere, increases its temperature (1 K), increases the temperature difference with the poles at that height and shifts the jetstreams polewards, including the connected wind-, cloud- and rainpatterns. That is reflected in river flows. Several findings show the correlations:
http://www.erh.noaa.gov/box/effects.htm
http://onlinelibrary.wiley.com/doi/10.1029/2005GL023787/abstract (rivers in Portugal)
http://ks.water.usgs.gov/pubs/reports/paclim99.html (Mississippi catch area)
similar correlations were found for the Nile (Egypt), Po (Italy) and South African rivers, but the URL’s I had don’t work anymore…
The main article that shows the UV-jetstream connection is not on line anymore, but I have several others which connect solar cycles, stratospheric influences and weather/climate on earth:
http://www.nwra.com/resumes/baldwin/pubs/SolarCycleStrat_TropDynamicalCoupling.pdf
http://onlinelibrary.wiley.com/doi/10.1029/2005GL024393/abstract
http://www.sciencedaily.com/releases/2003/09/030926070112.htm
A lot of stuff to analyse for you…

Greg Goodman
June 7, 2014 1:05 am

Interesting work as always Willis.
Cross-correlation is a good start. I suggest you run some kind of FT on that. Just by eye I’d say that in fig2 you have a strong component about 11y mixed with something longer >20y

Jimmy Haigh
June 7, 2014 1:07 am

How does the solar cycle correlate with the orbit of Jupiter (11.86yrs)? Or perhaps the combined effect of Saturn and Jupiter which come together every 22 years or so?

June 7, 2014 1:08 am

Henry says
http://wattsupwiththat.com/2014/06/06/sunspots-and-sea-surface-temperature/#comment-1656267
Henry says again
so sorry, that one sentence should read
27 weather stations NH + 27 weather stations SH, balanced to zero latitude and 70/30 @sea/inland)

Patrick
June 7, 2014 1:12 am

“Jimmy Haigh says:
June 7, 2014 at 1:07 am ”
How dare you! We know, in computer simulations, that only CO2 drives climate on this rock and only that esitmated ~3% of ~390ppm/v at that from driving cars and using lights etc.
I think a /sarc off tag is not require here.

richard verney
June 7, 2014 1:13 am

At the crux of the point raised by Willis is that all the various data sets that are used in climate science are not fit for purpose. Unfortunately, this is not sufficiently recognised and/or accepted by the scientist who seek to use those data sets.
Unfortunately, they are all either of too short a duration, and/or have too wide an error margin and/or not enough sample saturation and/or are horribly bastardised by dropouts, pollution by UHI and/or endless bastardisation caused by adjustments made to the data set, the need for and correctness of which is moot.
This is one reason why one cannot see any first order correlation between the rise of CO2 levels and temperature in any of the instrument data sets. The signal from CO2 (if indeed there is any signal) is too small to be revealed in the noisy data sets that we have available, especially given the margin of error in the measurements undertaken.
If there is indeed manmade global warming, the only two data sets of note are the CO2 data set and ocean temperture data sets (ocean temperatures are a metric for energy absorption and hence imbalance, and the heat capacicty and energy stored in the oceans overwhelms that of the atmosphere by orders of magnitude).
Unfortunately, pre ARGO, there is no reliable ocean temperature data, and even post ARGO there are problems; first the adjustment made to ARGO data when it came on stream which data suggested that the oceans were cooling, second, the coverage – the oceans are vast and there are few ARGO buoys given the area and volume involved, and third, it is not known whether there is an in built bias caused by the free floating nature of the buoys which may have a tenedancy to be influenced by ocean currents which currents are themselves an artifact of variations in ocean temperature and/or density).
I am not surprised by Willis’ evaluation. It is what one would expect given the inadequacies of the available data sets, and the tendancy for scientists to over stretch the limits of the data available. Further the very nature of a coupled non linear chaotic system makes identification of trends and signals and corresponding responses extremely difficult to detect.

Charles Nelson
June 7, 2014 1:16 am

The ‘Global’ Sea Surface temperature anomaly in 1870 was positive ‘0.2C’
Let me just get this straight, you’re talking about the ‘year’ 1870 and you’re saying that somebody measured the ‘global’ sea surface temperature to within 1/10 of a degree C back then and came up with the 0.2C anomaly?

Greg Goodman
June 7, 2014 1:21 am

The presence of a longer term periodic change would also explain why the 11y “folding” (which is a pretty inappropriate term since it implies some kind of reversal) ends up with just noise. If the long period is near 22y using that as the offset may be more appropriate.
Frederick Michael says:
“Shouldn’t the sunspots (or whatever the real solar driver is) drive the FIRST DERIVATIVE of temperature, not simply the temperature? ”
Indeed. The primary effect of a radiative forcing is dT/dt as can be seen by the physical dimensions. Radiation flux is power ; temp is energy. They are orthogonal, so the initial investigation should be rad (SSN) vs temp.
If there is an effect it shoud accumulate but integrating with the huge capacity of the oceans will great smooth out any signal to the point where Willis’ one-size-fits-all 0.2 significance test will fail.
There is auto-correlation in temperature for precisely this reason. Willis makes reference to it on two occassions but seems imply that the results will be even worse if he accounted for autocorrelation, without saying why.
The most current way to remove autocorrelation is by taking the first different. This would in fact be dT/dt !

richard verney
June 7, 2014 1:21 am

Just a short point which is applicable to nearly all considerations regarding the effects of Solar irradiance, one cannot properly consider this in the absence of reliable data on cloud cover.
Until we know the extent of cloudiness over time (area, volume, composition, height of cloud stack, time of formation, duration of formation, place of formation, the underlying albedo which is being shielded by cloud cover, the surface type below the cloud cover and its absorption characteristics etc), one cannot reasonably consider how much energy is being imparted to the surface and without that one cannot begin to consider what sort of response one is expecting to see.

Patrick
June 7, 2014 1:34 am

“Charles Nelson says:
June 7, 2014 at 1:16 am”
That’s rather inconvenient. NOAA say they “know” what the global average sea and land temperatures were in 1880. I dunno, sounds like it was made up to me.

Santa Baby
June 7, 2014 1:43 am

“That only leaves two options for 0.8C in 150 years. Internal variability or solar variability. Solar variability is prime suspect. All you need to understand is that water is not a “near blackbody” or even close.”
There has been to much UHI and political motivated correction of the data sets. First one will have to remove these before one can use the data to find a correlation with anything.
Before the previous. IPCC report the Jones et al showed the arctic North of 70 deg North to have been as warm or warmer in the 1930s. That changed drastically overnight with a new data set.
If arctic really is now warmer than in the 1930s, then I find it strange that the global temperature is much higher than in the 1930s. UHI and political motivated corrections?

June 7, 2014 1:55 am

‘Although it’s not clear what “we” means when he uses it’
That’s the Royal “We”. We use it ourselves, in our sole-authored papers.

Greg Goodman
June 7, 2014 2:32 am

http://climategrog.wordpress.com/?attachment_id=956
cross-correlation of monthly global SST and SIDC monthly SSN.
As I suspected a notable circa 22y peak and “11y” is split into fine structure as is pretty much universally found, this is not a single peak. Closer read-off here gives : 10.12 and 11.22 y.
The largest peak is at 170y and is ten times the magnitude of the peaks show in this detail.
Usual caveats about data length etc apply. But that was the long period found in SSN in the chinese paper featured yesterday on WUWT. It appears also in cross-correlation with global SST as the strongest signal.
I’m curious that peaks appear to be close to being multiples 5.5 11,22,33,44,66

Mick
June 7, 2014 2:33 am

“….smaller secular variations in solar strength can have a significant effect on the climate…”
I have a problem with the words ‘smaller’ and ‘significant’ …… ‘smaller’ is the TSI variation, because of the huge output of the Sun….. the effect ‘significant’ only for humans who want to be comfy in a ‘narrow’ range of climate…. at the moment global warming is ~ 0.5deg extra….. well 300K or 300.5K ….. bugger all difference …. but ‘significant’ for humans….

June 7, 2014 2:52 am

The correlation between Earth Sea & Land Temps is from 22 year Magnetic Cycles NOT 11 year periods, why do you insist to show the 11 year Solar Cycles when it doesn’t show/prove anything as you have now demonstrated. Wills please go back to the drawing board and re work this article, I’m sure your find what your looking for

David McKeever
June 7, 2014 2:52 am

myline=strsplit(discrets(as.vector(spotgauss),collapse=T),split=””);myline (line 43 of shavivcorrelations.R) made my RStudio squawk. I couldn’t see a discrets() or discretes() function in your Willis Functions, and a search showed some possibles discretes() in the ggplot package.

ren
June 7, 2014 3:31 am

HenryP
here is clear the magnetic activity of the Sun and the Earth’s magnetic field.
http://www.cpc.ncep.noaa.gov/products/stratosphere/strat_a_f/gif_files/gfs_t10_sh_f00.gif

herkimer
June 7, 2014 3:31 am

Willis
Have you looked at this ?
Graph below is a detrended historical plot of the sea surface temperature anomalies (HADSST3) for the Pacific and Atlantic Ocean basins from pole to pole The peaks and valleys of this plot match the peaks and valleys of global atmospheric cooling and warming periods over the last 130 years . The surface temperatures of these oceans have peaked and are again heading for a cold trough by about 2040/2045 like they did 1910 and 1975. A global warming peak like we recently had is not predicted for 65- 70 years or until 2075/2080. The source of this cooling is the Global oceans Meridonal Overturning Circulation or MOC When there is a stronger than normal MOC, there is more deep cold water upwelling into the oceans by means of ocean conveyor belts. This will ultimately cool the SST and cool the Arctic as is already happening.
Courtesy of Bob Tisdale’s and WUWT web pages
http://bobtisdale.files.wordpress.com/2013/07/figure-72.png
If we hind cast the above ocean graph and in particular the 70 year Atlantic Ocean SST, pole to pole , we find that major SST troughs like 1905/1910 and 1975 could have also happened in 1835, 1765, 1695 and major peaks in SST like 2010 and 1940 could have happened in 1870, 1800, 1730 and 1660.
For example the North Atlantic Ocean may have been cooling during the following past periods [And probably the Pacific as well.] The major solar minimum period is also noted
1940 to 1975
1870 to 1910[Minimum 1880-1910]
1800 to 1835[Dalton minimum 1790-1820]
1730 to 1765
1660 to 1695 [Maunder minimum 1645-1715]
1590 to 1625
1520 to 1555 [Sporer minimum 1460-1550]
1450 to 1485 [ Sporer minimum 1460-1550]
These cooler Atlantic Ocean SST periods correspond to the historic low CET temperatures and just happen to occur during the Maunder, Dalton and Modern Minimums of 1645-1715, 1790- 1820, and 1880-1910. In another words the reason for the low CET temperatures could have been the cool Atlantic SST and not because of the changing solar cycle during each of the three major solar minimums.
This changing Atlantic Ocean pattern can be seen in this Reconstructed North Atlantic SST between 1567 and 1990 with the courtesy of Bob Tisdale’s web page
Courtesy of Bob Tisdale
http://bobtisdale.blogspot.ca/2008/07/sst-reconstructions.html
http://i36.tinypic.com/wld5kl.jpg

ren
June 7, 2014 3:41 am
ren
June 7, 2014 3:48 am

Now let’s look at the ocean temperature anomalies.
http://weather.unisys.com/surface/sst_anom.gif

June 7, 2014 4:01 am

My impression is that these types of studies are excellent examples of what is known as “…torturing and molesting…” the data.

June 7, 2014 4:38 am

RACookPE1978 says
But!!!! I do NOT know what will happen due to that change.
So, to cover for that lack of knowledge, I would prefer to focus on the earlier longer-term 66 year patterns of “several high, several low” cycles we see since 1650 as the earth warms from the LIA. Do those cycles matter?
henry says
we can measure the change if we take a balanced sample of weather stations of the world as shown earlier up this thread, and determine the change in temperature per annum
(which Greg also refers to)
e.g
Here are my latest results for the change in the speed of minimum temperatures (27 weather stations NH + 27 weather stations SH, balanced to zero latitude and 70/30 @sea/inland)
last 40 years (from 1974) +0.004 degree C/yr
last 34 years (from 1980) +0.007 degree C/ yr
last 24 years (from 1990) +0.004 degree C/yr
last 14 years (from 2000) -0.009 degree/yr
Now, note that the observed values are very low, indeed, yet it seems they are significant.
Namely, setting the periods out against the speed of warming/cooling I get a binomial again with rsquared equal to 1 (100% correlation)
There is no error in the equation…..
Hence, there is no AGW… There is no room for it in my equation.
One is tempted to think that we can project on this binomial forward, which would imply more cooling coming up ahead. Indeed, I think some more cooling is still coming up ahead. But we know from various investigations of mine, including ozone increase and the evaluation of solar magnetic field strengths, that we must come to a dead end stop on that binomial. Everything points to 2015 or 2016 as the date for the dead end stop of the process that causes the cooling on earth (coming from a variance of the sun’s output)
http://blogs.24.com/henryp/2013/04/29/the-climate-is-changing/
http://www.nonlin-processes-geophys.net/17/585/2010/npg-17-585-2010.html
which suggests a 87 or 88 – and a 208 year cycle when we look at energy coming in
e.g. also
Persistence of the Gleissberg 88-year solar cycle over the last ˜12,000 years: Evidence from cosmogenic isotopes
Peristykh, Alexei N.; Damon, Paul E.
Journal of Geophysical Research (Space Physics), Volume 108, Issue A1, pp. SSH 1-1, CiteID 1003, DOI 10.1029/2002JA009390
Among other longer-than-22-year periods in Fourier spectra of various solar-terrestrial records, the 88-year cycle is unique, because it can be directly linked to the cyclic activity of sunspot formation. Variations of amplitude as well as of period of the Schwabe 11-year cycle of sunspot activity have actually been known for a long time and a ca. 80-year cycle was detected in those variations. Manifestations of such secular periodic processes were reported in a broad variety of solar, solar-terrestrial, and terrestrial climatic phenomena. Confirmation of the existence of the Gleissberg cycle in long solar-terrestrial records as well as the question of its stability is of great significance for solar dynamo theories. For that perspective, we examined the longest detailed cosmogenic isotope record—INTCAL98 calibration record of atmospheric 14C abundance. The most detailed precisely dated part of the record extends back to ˜11,854 years B.P. During this whole period, the Gleissberg cycle in 14C concentration has a period of 87.8 years and an average amplitude of ˜1‰ (in Δ14C units). Spectral analysis indicates in frequency domain by sidebands of the combination tones at periods of ≈91.5 ± 0.1 and ≈84.6 ± 0.1 years that the amplitude of the Gleissberg cycle appears to be modulated by other long-term quasiperiodic process of timescale ˜2000 years. This is confirmed directly in time domain by bandpass filtering and time-frequency analysis of the record. Also, there is additional evidence in the frequency domain for the modulation of the Gleissberg cycle by other millennial scale processes.
end quote
hope this helps

June 7, 2014 6:22 am

There is something fascinating about science. One gets such wholesale returns of conjecture out of such a trifling investment of fact.
Mark Twain
US humorist, novelist, short story author, & wit (1835 – 1910)

Greg Goodman
June 7, 2014 4:45 am

Here is the correlation function of SST and SSN from which I derived the spectrum I posted above.
http://climategrog.wordpress.com/?attachment_id=958
There is a rather broad peak in correlation at a lag of about 10 years and an equally strong, but more focused correlation at just over 21 years. This explains why Willis’ extension of the 11y “folding” idea shows nothing of interest. It does disprove either the circa 11 or 22y cycles or the presence of a solar signal. In fact is was a fairly sure way to destroy what is there. ( This was not Willis’ own idea, he was extending a technique used by Nir Shaviv. )
It should also be noted that is a clear anti-correlation with period of about 140 years and a lag of half that. That is a period of time, there is not enough data to suggest this is periodic as in cyclically repetitive.
Even this cursory investigation seems enough to suggest there is a correlation between SST and solar activity represented by SSN.

Genghis
June 7, 2014 5:03 am

Willis, I am living on a Sailboat in the Bahamas. The surface temperature as measured by my IR gun for the entire last week was 80.4˚ F. And today since the wind has quit blowing the Surface temperature jumped to 84.6˚ F. The surface temperature is incredibly consistent 24 hours a day as long as the winds are consistent.
The ocean surface temperatures are controlled almost entirely by windspeed (evaporation rate). Clouds, Sunlight, clear sky, and night have no effect on the surface temperature.
Sure there are other things that affect the surface temperature, length of day, currents, rain, barometric pressure, but they are minor. The dominant factor is the wind.
If you think about it, this observation explains the UHI, Global warming and disproves climate change.

June 7, 2014 6:18 am

An IR gun. Calibrated? What’s the emissivity of the sea surface? Cross verified with a good old mercury in glass?

June 7, 2014 5:25 am

Hi Willis,
Despite being a regular reader here and at other climate blogs, I’ve not before come across the correlation between solar irradiance and poleward energy flux that Botkin recently put up as evidence to the Senate (of solar influence). I assume this is related to the (paywalled) paper below? (all I could find on a quick search). I’m not a climate dude so haven’t the tools to investigate. Have you come across this before and do you have any opinion on the apparent correlation? I can see by eye a couple of obvious deviations, but these could be volcanoes or something. No worries if I’m opening another can of worms you don’t want to look inside of 😉
Solar irradiance modulation of Equator-to-Pole (Arctic) temperature gradients: Empirical evidence for climate variation on multi-decadal timescales: Willie Soon and David R. Legates, 2013.

AJ
June 7, 2014 5:44 am

I just came across this yesterday. From climateaudit:
http://climateaudit.org/2007/02/11/holgate-on-sea-level/

Update: In response to an inquiry from a CA reader, Holgate gave the following response on solar/sea level connections:
Holgate’s response:
Many people have tried to link climate variations to sunspot cycles. My own feeling is that they both happen to exhibit variability on the same timescales without being causal. No one has yet shown a mechanism you understand. There is also no trend in the sunspot cycle so that can’t explain the overall rise in sea levels even if it could explain the variability. If someone can come up with a mechanism then I’d be open to that possibility but at present it doesn’t look likely to me.
If you’re interested in solar cycles and sea level, you might look at a paper written by my boss a few years back: Woodworth, P.L. “A world-wide search for the 11-yr solar cycle in mean sea-level records.” Geophysical Journal of the Royal Astronomical Society. 80(3) pp743-755
You’ll appreciate that this is a well-trodden path. My own feeling is that it’s not the determining factor in sea level rise, or even accounts for the trend, but there may be something in the variability. I’m just surprised that if there is, it hasn’t been clearly shown yet.

June 7, 2014 6:21 am

IPCC AR5 Figure 13.6
According to satellite telemetry GMSL between 2005 and 2012.5 increased about 20 mm. That’s about 0.75 of an inch. At that rate the sea level will increase another 8.25 inches by 2100. That won’t be a problem for anybody not dumb enough to currently live or build 4 inches above GMSL. Might need your high water pants.
What sea level rise are you referencing? Something IPCC doesn’t know about?

Nick Yates
June 7, 2014 5:44 am

Richard Verney says:
When considering this, one has to bear in mind that the heat flux is upwards in the first few millimetres of the ocean such that energy absorbed in the first few microns cannot find its way downwards by conduction
I was just wondering, as water is at it’s densest at 4C, could this make any difference, perhaps nearer the poles?

peter bartner
June 7, 2014 5:48 am

From a scientist who has read extensively in the field of climate
I would think that the Sun would act mainly through its interactions with our oceans; primarily with UV photons that get by the ozone layer. Visible will also contribute. During the decline of the last solar sunspot cycle, UV radiation declined 6% which should have an impact on ocean temperatures. This mechanism, because of the slow response time of these vast reservoirs, will not respond quickly enough to reflect Sun spot cycles, thus, there would be observable sun spot pattern. .

David L. Hagen
June 7, 2014 6:15 am

Sea Surface Temperature vs Integral of Total Solar Insolation
Willis. Try comparing Ocean Surface Temperature vs the INTEGRAL of TSI (or sunspots) rather than directly.
Frederick Michael asks: “Shouldn’t the sunspots . . . drive the FIRST DERIVATIVE of temperature, not simply the temperature?”
Greg Goodman affirms: “If there is an effect it should accumulate but integrating with the huge capacity of the oceans will great smooth out any signal”.
See David Stockwell who models and quantitatively shows temperature varies not directly but as the integral of solar flux, with a phase lag of Pi/2 (90 degrees) i.e. 2.75 years lagged from the ~11 year sunspot cycle.
Stockwell shows that the direct correlation of solar irradiance with temperature R^2 is only 0.028 while the cumulative solar irradiance has a correlation R^2 of 0.72 and solar + volcanic has R^2 of 0.78. See Fig. 4 in
David R.B. Stockwell “On the Dynamics of Global Temperature” August 2, 2011 http://vixra.org/abs/1108.0004
David R.B. Stockwell, “Accumulation of Solar Irradiance Anomaly as a Mechanism for Global Temperature Dynamics” 9 Aug. 2011
http://vixra.org/abs/1108.0020

Here is presented a novel empirical and physically-based auto-regressive AR(1) model, where temperature response is the integral of the magnitude of solar forcing over its duration, and amplification increases with depth in the atmospheric/ocean system. The model explains 76% of the variation in GT from the 1950s by solar heating at a rate of $0.06\pm 0.03K W^{-1}m^{-2}Yr^{-1}$ relative to the solar constant of $1366Wm^{-2}$.

David R.B. Stockwell, “Key evidence for the accumulative model of high solar influence on global temperature” 4 August 23, 2011 http://vixra.org/pdf/1108.0032v1.pdf

Firstly, variations in global temperature at all time scales are more correlated with the accumulated solar anomaly than with direct solar radiation. Secondly, accumulated solar anomaly and sunspot count fits the global temperature from 1900, including the rapid increase in temperature since 1950, and the flat temperature since the turn of the century. The third, crucial piece of evidence is a 90 deg shift in the phase of the response of temperature to the 11 year solar cycle. These results, together with previous physical justifications, show that the accumulation of solar anomaly is a viable explanation for climate change without recourse to changes in heat-trapping greenhouse gasses.

Stockwell further shows a 2.75 year Phase Shift in Spencer’s Data
Sunspots are an approximate measure of “Total Solar Insolation”.
Richard Verney makes another critically important point in insolation AFTER cloud effects – where there is very sparce uncertain data. David Stockwell highlights the importance of the insolation temperature phase lag to address Spencer’s challenge on whether:

1. Changes in cloud cover actually do drive changes in global temperature due to gamma-ray flux (GRF) or other effects, or
2. The changes in cloud cover are caused by changes in global temperature, with the derivative mechanism described above.
3. Both 1 and 2.

CO2skeptic’s note on the 22 year Hale cycle instead of 11 year Schwab cycle may be significant.

June 7, 2014 6:24 am

richard verney says:
June 7, 2014 at 12:49 am
————————————
You raise valid points regarding ocean spray and near surface saturated air. However while this H2O stops most DWLWIR from the atmosphere reaching the ocean surface, it is itself emitting LWIR back to the surface. There are two questions here, the effect of incident LWIR on the cooling rate of water and the effective emissivity of water.
Empirical experiment proves DWLWIR cannot heat nor slow the cooling rate of water that is free to evaporatively cool. That’s game over for DWLWIR slowing the cooling rate of 71% of Planet Ocean’s surface. You say “sorry Willis”. You wouldn’t say that if you saw what he wrote at Talkshop in 2011. Willis did not lose the debate to me. He lost to a roll of microwave safe cling wrap. That’s just sad.
And the effective emissivity of water? This is one of the church of radiative climastrology’s greatest “mistakes”. I have recently run some IR measurement experiments of warm water under a cryo cooled “sky”. An emissivity setting above 0.95 works well for measuring water temp in a sea of environmental IR. Eliminate this background IR and I find that you need an emissivity setting below 0.8 for accurate reading. I am beginning to suspect the old texts claiming IR emissivity of 0.67 may be correct.
What does this mean?
The ability of water to absorb UV/SW/SWIR is around 0.92. It’s ability to radiate LWIR could be as low as 0.7. Without evaporative cooling our oceans would become a giant evaporation constrained solar pond with temps topping 80C. The atmosphere is provably cooling 71% of the planets surface.
What is the only effective cooling mechanism for the atmosphere?
There is only one logical conclusion –
97% of climastrologists are assclowns.

Greg Goodman
June 7, 2014 6:43 am

David L. Hagen says:
Sea Surface Temperature vs Integral of Total Solar Insolation
It’s essentially the same as dT/dt vs SSN.
differentials amplify the short term signals , integrals smooth them out.
I redid the power spectrum using d/dt(SST) and it’s essentially the same, though I had to filter out the annual variation in SST to resolve the circa 10 and 11y peaks from one another.
One thing that is a surprise is a fairly strong peak at about 9.04 to 9.09 . I also found this while discussing another Willis thread that looked at correlation of sea level and SSN.
I had previously been inclined to think this peak in SST was a lunar tidal effect, but seeing present in these two cases of cross-correlation with SSN suggests it too is solar in origin.
Another pointer to the “fundamental connectedness of all things” to quote Douglas Adam’s Dirk Gently.
This 9.04 is also found in cross-correlation of AMO and PDO (BEST, Curry) and directly in N.Alt and N.Pacific SST. (me).

Greg Goodman
June 7, 2014 6:59 am

IIRC BEST/Curry paper reported 9.1 +/- 0.4 y , a rather large and cautious uncertainty from Monte Carlo chopping and changing techniques.
I found the peak to be centred on 9.05 in that case ( N.Alt and N.Pacific SST)
http://climategrog.wordpress.com/?attachment_id=754
This would seem to be the same thing as Scafetta’s 9.01 +/-0.1y

Greg Goodman
June 7, 2014 7:01 am

Oops. This would seem to be the same thing as Scafetta’s 9.1 +/-0.1y

ren
June 7, 2014 7:28 am

Someone will say an increase of neutrons of a few percent is not much. Is it really?
Primary cosmic rays are a stream of particles with energies from 10^7 to about 10^20 eV reaching the vicinity of the Earth from interstellar space. It consists of different types of particles: electrons and positrons, protons, alpha particles and heavier nuclei (up to uranium) and gamma quanta with high energy. This radiation does not reach directly to the surface of the Earth and can be seen above the Earth’s atmosphere on satellites or balloons.
The particles of primary cosmic rays entering the Earth’s atmosphere to produce particles called avalanche. secondary cosmic radiation, which is part of the natural radioactivity observed on the surface of the Earth.
Secondary cosmic rays reaching the Earth’s surface consists mainly of muons. Muons are unstable elementary particles very similar to electrons but 200 times heavier. Formed in the atmosphere mainly from the decay of another type of elementary particles, mainly risers and kaons. These in turn are created in the collisions of particles of primary cosmic rays with the atmosphere or the collisions of secondary particles created in the previous collisions.
The muons have an average life of at rest about 2 * 10^-6 seconds (2 microseconds). The muons decay into electrons or positrons and neutrinos. Muons are very penetrating particles (eg if they have energy above 5 billion electron volts, can penetrate more than 10 meters under the ground). With the electric charge can be easily recorded. These are ionizing particles.
The intensity of muons at the surface is about 200 particles per area of ​​1 square meter per second. This corresponds to the passage of particles about 6 per second by the head of a human, resulting in the head ionization approximately 100 million per second. It is natural radiation in our environment!

Jeff L
June 7, 2014 7:43 am

For those readers with a background in signal processing (especially geophysical processing), please take the time to read this post.
There is a gut feeling among many observers that the sun & solar cycles is somehow connected to climate. A reasonable hypothesis to want to explore , given that the sun ultimately powers our atmosphere.
Willis & others have shown that a solar signal isn’t readily discernible is various atmospheric / oceanic data sets. Perhaps the problem is the assumption of some sort of direct correlation.
Maybe a better mathematical model is a convolutional model ? The time series of some measure of solar activity would be the input signal. This would be convolved with an atmospheric “filter operator” with the output being an observed time series of atmospheric temperature. Since we have both the input signal (solar activity time series) and output series (atmospheric temperature time series), in theory , we could use a deconvolution process to solve for an atmospheric filter response operator.
This operator could then be tested against other datasets for viability in hindcasting and perhaps modified to come up with a better operator with better hindcasting ability. If the process worked, it could establish a connection between solar activity & temperature not readily visible through correlation or cross-correlation or any other spectral based approaches (because the spectra of the output signal would be different than the input signal, filtered by the atmospheric operator).
The spectral characteristics of the atmospheric operator may , in and of itself , provide deep insight into big picture atmospheric processes which have yet been unrecognized. There is an assumption that the operator is stationary but that could also be tested by deriving operators for different time periods. Perhaps there would be predictable variations in the operator with time. that would be useful in making forecasts of future temperature.
In short, there is a ton of potential research that could be done around the convolutional model & there is no telling just what insights could be gleaned until the research is done.
For any geophysicists out there, I am sure you can see the analogy here with seismic data. Input is your seismic source (analog = Solar activity time series) which is convolved with the Earth filter (analog = atmospheric filter ) , resulting in your observed seismic time series trace (analog = observed temperature time series).
I am not sure if anyone has pursued this type of research. I have always wanted to do this, but I simply do not have the time to pursue it. I would love it if someone would pick this idea up & run with it. it may work, it may not but I would be very curious to see the results. If someone chooses to pursue this idea based on this post, please just acknowledge where the idea originated.

Greg Goodman
June 7, 2014 8:00 am

David L. Hagen says: http://landshape.org/enm/phase-shift-in-spencers-data/
Stockwell : “Spencer argues that it is impossible to distinguish between 1 and 2. Both Spencer and Lindzen both consider the lags important because correlation is greatly improved (and determines whether feedback is positive to negative). Neither seem to have mentioned the 3 month phase relationships emerging from integral/derivative system dynamics. I can’t see how it is possible perform a valid analysis without this insight. ”
Indeed:
http://climategrog.wordpress.com/?attachment_id=884

Greg Goodman
June 7, 2014 8:03 am

“Maybe a better mathematical model is a convolutional model ? ”
See the above link. Exactly what I did with AOD.

David Riser
June 7, 2014 8:05 am

Willis,
I would propose that if you are right, that the temp has a significant regulating mechanism, then any correlation between SSN and any temp set would be very difficult to find as long as there is sufficient energy into the system. Obviously it occasionally gets pretty cold here on earth we have plenty of evidence of that and it gets a tiny bit warmer, there is some evidence of that. So I would propose that we wont have any statistical evidence of sun influence until we enter a period of significant temperature change. .8C just isn’t enough to be detectable. Just my thought. Love your work by the way.
v/r,
David Riser

Greg Goodman
June 7, 2014 8:09 am

Konrad says “Empirical experiment proves DWLWIR cannot heat nor slow the cooling rate of water that is free to evaporatively cool. ”
I suspect this may be correct but I’ve yet to see the “proof”. Can you point me to the proof you are referring to, it would be most useful to see some proof.

ferdberple
June 7, 2014 8:39 am

Where is the climate dataset that shows the ~11-year sunspot/magnetism/cosmic rays/solar wind cycle?
============
Perhaps it doesn’t exist because you are looking at the wrong information. the strength of the cycle varies inversely as the cycle length, and temperature integrates this signal.
thus, you will not see correlation at 11 years, except by accident. instead look for correlation between cycle length and inverse rate of temperature change.
ie; shorter cycles make it more warmer, longer cycles make is less warmer, as compared to average length cycles and historical trajectory of temperature.

ferdberple
June 7, 2014 8:42 am

any correlation between SSN and any temp set would be very difficult to find
============
looking for a correlation on a 11 year cycle is not the same as looking for “any correlation”.

Jeff L
June 7, 2014 8:46 am

Greg Goodman says:
June 7, 2014 at 8:03 am
“Maybe a better mathematical model is a convolutional model ? ”
See the above link. Exactly what I did with AOD.
——————
Very interesting analysis. 2 questions come to mind immediately :
1) Could the shape of the impulse response be applied for other volcanic events & associated AOD changes (or is each volcanic event have it’s own impulse response dependent on size of eruption, composition of ejecta, height of eruption, geographic location, etc)?
2) Could the same principle be applied to other forcings, such as solar variation or GHGs, the big difference being that the forcing isn’t a time spike like a volcanic eruption but a longer, time varying input ? (and of course , would it be possible to untangle various forcings or alternatively developing a net forcing time series & and figure out what the atmospheric filter is … if it does in fact exist).
It is encouraging that a convolutional model can be applied to AOD with meaningful results. it does suggest a convolutional model could be applied to other forcings as well.

ferdberple
June 7, 2014 8:48 am

Maybe a better mathematical model is a convolutional model
==========
for example, most would agree that the distance traveled in a car is related to the gas pedal. But often when the gas pedal is pressed hardest you are barely moving, and other times when your foot is off the gas is when you are traveling the fastest. So if one looks for simple correlation it may not be at all obvious that a relationship exists..

Greg Goodman
June 7, 2014 9:01 am

fred, don’t misquote by omission. What David Riser said was:
“I would propose that if you are right, that the temp has a significant regulating mechanism, then any correlation between SSN and any temp set would be very difficult to find as long as there is sufficient energy into the system. ”
There is strong regulation by negative feedbacks in the tropics, less so outside the tropics. That is why it was not difficult at all for me to find the correlation in the first SST dataset I used.
http://climategrog.wordpress.com/?attachment_id=958
There is a clear 10,11,21 year peaks in the power spectrum . There is also a very strong correlation on the centennial scale the peaks at a lag of about 15 years. This tells us something about the degree of temporal accumulation and the depths of water involved.
There are multiple, significant correlations present but anyone expecting a nice simple 11y pattern, invariant over centuries, to jump out and hand itself up on a plate is being incredibly simplistic, and showing little comprehension of the complexities of climate ( and solar ) variability.

ren
June 7, 2014 9:09 am

The effect of the current cycle is clearly visible in the growth of sea ice in the south. Moreover, the temperature of the ocean around Antarctica suggests a further progress of ice.
http://arctic.atmos.uiuc.edu/cryosphere/IMAGES/seaice.anomaly.antarctic.png
Please look at the year 2008 (an extremely low minimum) and an increase in ice.

June 7, 2014 9:14 am

“Willis & others have shown that a solar signal isn’t readily discernible is various atmospheric / oceanic data sets. Perhaps the problem is the assumption of some sort of direct correlation.”
PERHAPS THERE IS NO FRICKING PROBLEM
The sun varies by a small number of watts from peak to peak
The climate doesnt respond to these small variations.
AS IN DUH
occam says……

dp
June 7, 2014 9:23 am

The approximately 11 year solar cycle is the witnessed cyclic variation of solar characteristics caused by internal solar processes. It is impossible that these variations can have zero affect on the Earth and in fact all the planets. If that affect is undiscovered it is because we’re looking for the wrong evidence or it is lost in the noise. I would suggest that the entire affect is spread across so many regimes that it is lost in the noise. If one does not understand the mechanisms of conversion of solar cycles to phenomena and have available instruments to observe and validate those phenomena, the affect can never be discovered. That is were we are.
The consequences of 11 year solar variation are hidden in plain sight and we may never be able to isolate them. I think too that an 11 year cycle is unimportant because: there is no accumulative impact that we can identify, and, we have bigger fish to fry.
What we do see is correlation between variations in the ~11 year cycle over time to time varying terrestrial phenomena and that is important.

Greg Goodman
June 7, 2014 9:23 am

Jeff L says: Very interesting analysis. 2 questions come to mind immediately :
Once you have the system response it should be applicable to all “forcings” in similar circumstances. The nice thing about Mt P was that it was big enough to be distinguishable for all the rest that is going on. This at least gives us an estimation of how the system responds.
After that it can be applied to smaller, faster or slower variations. Note what I did was based on tropical data so should be applicable to tropical response to other equatorial volcanoes. It should be applicable to calculate the tropical response to slowly increasing GHG forcing and/or solar variability.
I think this is how the question should be being investigated. I’m still a little uncertain of things like at which point the additional SW input that is seen since AOD settled, starts to take effect. That is why it’s still labelled as a draft version.
The extra-tropical AOD data seems less complete which is why I have not gone into that yet.
I see two things from that so far, the relaxation model indicates earlier values of AOD forcing from 1992 that were based on atmospheric physics were correct and have just been jerry-rigged since to make the models work better without changing the _preconceived_ assumptions about positive feedbacks. Secondly, that there are strong negative feedbacks in the tropics which take out just about any “forcing” changes within a year or two.
A third thing which came out of that was the warming effect of volcanoes that apparently no one has “noticed” yet.
http://climategrog.wordpress.com/?attachment_id=955
An extra 2 W/m2 of SW is significant in all this.

Greg Goodman
June 7, 2014 9:27 am

dp says : “The consequences of 11 year solar variation are hidden in plain sight and we may never be able to isolate them. I think too that an 11 year cycle is unimportant because: there is no accumulative impact that we can identify, and, we have bigger fish to fry. ”
HUH? I just have. I’ve also ‘isolated’ a centennial scale signal that kinda needs to taking into account before wetting the bed every night for fear that they sky will burn tomorrow.

Pamela Gray
June 7, 2014 9:27 am

This seems plain to me. If the data has to be juggled, folded, sieved, lagged, stretched, pulled, and cut into bite size pieces of taffy in order to see a solar affect, wouldn’t that lead one to conclude that natural noisy intrinsic variation swallows a solar affect so completely that it can be appropriately disregarded in the search for a temperature trend driver? Am I missing something?
The Earth, with its many ways of storing and belching heat, seems quite capable of hourly, daily, seasonally, and long termally (backdoor alliteration is more fun than plain ol’ alliteration) changing the temperature all by itself-ally.

Greg Goodman
June 7, 2014 9:41 am

@Jeff L BTW the same principal should be applicable to work out CO2 / SST relationship. Rising SST will cause a degree of out-gassing. I don’t think anyone has properly assessed this yet. Murray Salsby sounded like he had something to present but never did.
He was sounding like he was saying it was all due to out-gassing which I think is improbable, just as improbable as ignoring it being the right answer 😉
The interplay of the both orthogonal in-phase responses are equally important. Neither can be left out.
http://climategrog.wordpress.com/?attachment_id=399
I started to investigate the CO2 question here:
http://climategrog.wordpress.com/?attachment_id=625

Greg Goodman
June 7, 2014 9:44 am
Greg Goodman
June 7, 2014 9:48 am

Pamela Gray: “Am I missing something? ”
Most likely all the stuff above you are choosing to ignore, in continuing with conclusions you’d already made.

Greg Goodman
June 7, 2014 9:51 am

” If the data has to be juggled, folded, sieved, lagged, stretched, pulled, and cut into bite size pieces of taffy in order to see a solar affect…..”
Try cross-correlation, much quicker.
http://climategrog.wordpress.com/?attachment_id=958

June 7, 2014 9:57 am

Something I have heard of affecting weather is the 22 year Hale cycle, which the 11-year cycle is a half-cycle of. The sun’s magnetic polarity flips one way during one 11-year cycle, and flips back during the next. One thing that seems to happen every other minimum of the 11-year cycle is notably harsh winters from eastern North America to northwestern Europe. This does seem to be mostly a regional effect, whose impact on global temperature datasets is likely to be insignificant.
Another solar variation issue could be the mass of the oceans smoothing out the 11-year cycle more than longer period ones.

Greg Goodman
June 7, 2014 9:58 am

Now I said earlier I was curious about the harmonic nature of the long term periods.
http://climategrog.wordpress.com/?attachment_id=956
This seems to reflect the more or less triangular up and down ramps in the cross correlation function. This reminds me of the “acceleration” reported in the recent Jevrejeva paper on global sea level, that turned out be not a long term acceleration as suggested in the abstract but a rather sudden change of direction around 1850-1870.
Add the 130-140 year period of the SST/SSN correlation to that and we see it points to the present. May be something to look into.

Matthew R Marler
June 7, 2014 10:01 am

This was a good, straightforward focused analysis on a single research hypothesis. If sunspots affect earth surface temperature, the effect appears somewhere else. It is helpful sometime to absorb simple results before trying to rescue the research hypothesis by rewriting it.
thanks again.

Pamela Gray
June 7, 2014 10:14 am

Greg I’ve read your stuff. Your stuff actually prompted the allegorical back-door alliterated reference to making taffy. The ingredients are the same beginning to end. The taffy shape and texture is what humans do to boiled sugar and water.
Earth’s climate and weather beginning to end is boiled sugar and water. Solar enthusiasts love to manipulate it to make it look different than what it is: a piled mound of boiled sugar and water.

Genghis
June 7, 2014 10:22 am

Nicholas Schroeder, I have two IR Guns, both from Lowes the cheaper version and the more expensive one, Southwire is the name brand and yes they are very accurate when compared to the engine gauges, refrigerator, oven, engine intake, exhaust, water salinity gauge, cooking thermometer, etc. and yes mercury gauges. It is amazing how many thermometers I have on board.
The bottom line though, and I have tested it with the cooking thermometer, the surface temperature of the ocean does not change due to the daily solar cycle, clouds, lack of clouds, etc.
The surface temperature responds directly to wind speed (evaporation), almost exclusively.
Direct solar radiation, not to mention back radiation has zero effect on the surface temperature. The only effect insolation has on the surface temperature is on how quickly the surface temperature responds to changes in wind speed.
I have been studying this for two years now from the States down through the Bahamas, to the Bottom of the Caribbean. I am currently in Georgetown and the surface water temperature is 82.2 degrees and it was 82.2 degrees this morning before dawn. We had a little squall come through and the temperature dropped a few degrees while it was raining, but immediately jumped back up after the squall passed.

dp
June 7, 2014 10:44 am

HUH? I just have. I’ve also ‘isolated’ a centennial scale signal that kinda needs to taking into account before wetting the bed every night for fear that they sky will burn tomorrow.

Let us know when you’ve isolated the 11 year cycle that is the topic of this article.

Greg Goodman
June 7, 2014 10:59 am

dp: “Let us know when you’ve isolated the 11 year cycle that is the topic of this article.”
Let me know when you’ve read what I’ve posted so far.

Greg Goodman
June 7, 2014 11:02 am

Pam, thanks for the cookery lessons and literary diversions. Don’t hesitate to come back if you have anything to say pertaining to science.

ralfellis
June 7, 2014 11:06 am

Willis.
I seem to remember many years ago on this site, someone saying that the length of the sunspot cycle was more important regards climate, rather than the number of spots.
Would it be worth renewing the analysis, using cycle-length as the primary criteria?
Cheers,
R

James
June 7, 2014 11:09 am

Frederick, Greg, and others,
I just wanted to lend my support for the integral/derivative relationship between flux and temperature. I have had success modeling the integral of flux vs. temperature, and it’s a reasonable assumption.
Computationally, there are benefits to integration vs. derivatives (the integral is just the sum), but mathematically, the fundamental theorem of calculus ensures us that we should be able to go either way.

Greg Goodman
June 7, 2014 11:17 am

Steven Mosher says:
June 7, 2014 at 9:14 am
“Willis & others have shown that a solar signal isn’t readily discernible is various atmospheric / oceanic data sets. Perhaps the problem is the assumption of some sort of direct correlation.”
PERHAPS THERE IS NO FRICKING PROBLEM
The sun varies by a small number of watts from peak to peak
The climate doesnt respond to these small variations.
AS IN DUH
occam says……
==============
Occam says…. hand-waving and razors don’t mix.
http://climategrog.wordpress.com/?attachment_id=956
If Willis finished the job and did a FT of the correlation he performed, he probably would have found a similar result. The degree of correlation was probably not helped by Shaviv’s choice of an over-processed, interpolated “ice and sea” dataset but just by eye I could see enough to suspect what I found when I looked in detail.
Sure, there’s no fricking problem. There’s a correlation matching circa 10,11,22, and centennial changes in SST and SSN. What’s the fricking ?
That’s just an interested result. That could only be / not be a “FRICKING PROBLEM” if someone had an agenda and and entrenched position to defend.
I just find it interesting because previous poking around had not produced such a clear result.
Willis’ attempt to reproduce Shaviv 2008 was interesting and informative too.

Jimmy Haigh.
June 7, 2014 11:29 am

Jupiter? Jupiter & Saturn? 11.86 years & +/- 22 year cycles round the sun (wrt the Earth)? No takers?

ossqss
June 7, 2014 11:30 am

Speaking of sunspots, just got an alert that there is some activity going on. 3 rapidly developing spots pointing towards earth this weekend. One has X level character (AR2080)
The CME from the 4th just came through.
http://sdo.gsfc.nasa.gov/
http://stereo-ssc.nascom.nasa.gov/beacon/beacon_secchi.shtml

milodonharlani
June 7, 2014 11:43 am

Willis states, “What I am saying is that I still haven’t found any convincing sign of the ~11-year sunspot cycle in any climate dataset, nor has anyone pointed out such a dataset.”
Zhou & Tung (2013) found the cycle in their data set, ie tropospheric temperature observations. In a prior post, I read your questions about this paper, apparently based upon its abstract, but IMO the whole article is worth actually reading. Doing so would help answer your questions & respond to your general objections to “reanalysis”:
http://journals.ametsoc.org/doi/abs/10.1175/JAS-D-12-0214.1
It costs $35. I’d send it to you except for this: “The article you are purchasing is protected by United States copyright law and may not be reproduced, distributed, displayed, or republished without the prior written permission of the Publisher and/or the copyright holder. The copyright holder is indicated on the front page of the article.” Greg Goodman June 7, 2014 12:00 pm Just for completeness, I thought I run hadISST “reanalysis” data through the same processing. http://climategrog.wordpress.com/?attachment_id=959 Not hugely different though they seem to have fuzzed out some (most) of the detail in the -10 to +10y lag range. Greg Goodman June 7, 2014 12:01 pm “Gotta say, Greg, ” Gotta say Willis , quote what I said , not what you think I said etc….. Greg Goodman June 7, 2014 12:10 pm Greg Goodman says: June 7, 2014 at 4:45 am It should also be noted that is a clear anti-correlation with period of about 140 years and a lag of half that. That is a period of time, there is not enough data to suggest this is periodic as in cyclically repetitive. Greg Goodman says: June 7, 2014 at 2:32 am The largest peak is at 170y and is ten times the magnitude of the peaks show in this detail. Usual caveats about data length etc apply. If you disagree with someone, myself included, please QUOTE THE EXACT WORDS YOU DISAGREE WITH. This prevents many flavors of misunderstanding, and lets us all see just what it is that you think is incorrect. 😉 Greg Goodman June 7, 2014 12:32 pm W: “For example, try running cross-correlations of the sunspot data with random red noise … you’ll get peaks at ~11-year intervals. ” That is correct, and it will represent the strength of the 11 y component in both SSN and the red noise. If you think a lagged cross-correlation is meaningless, don’t do it. You throw a 0.2 “significance” line across your CC . Both my ICOADS and hadISST plots show 11 and 22 y lagged peaks above that level. Showing significance by the criterion you adopt. Yet you seem to think there’s not a significant signal. http://climategrog.wordpress.com/?attachment_id=958 http://climategrog.wordpress.com/?attachment_id=959 Actually a more rigorous effort should be made since one-size-fits-all does not count for determining significant levels of correlation. I’ll see if I can come up with something since that should be on my plots too. Using 0.2 everywhere is an error I’ve pointed out before that you have not addressed beyond trying to throw the ball back in my court and carry on using 0.2 whatever length and nature of data is. Greg Goodman June 7, 2014 12:43 pm W: “…. the data you are analyzing looks like this:” Fair point, but no. You’ve used “at least 30%” default option. I should have stated in the description somewhere that I used “at least 2%” coverage, to get a fuller set. I also have a script which fills minor breaks. So, fair pick, thanks for pointing it out. But no, the data I’m processing is not a broken mess. kadaka (KD Knoebel) June 7, 2014 12:46 pm From milodonharlani on June 7, 2014 at 11:43 am: Zhou & Tung (2013) found the cycle in their data set, ie tropospheric temperature observations. In a prior post, I read your questions about this paper, apparently based upon its abstract, but IMO the whole article is worth actually reading. Doing so would help answer your questions & respond to your general objections to “reanalysis”: http://journals.ametsoc.org/doi/abs/10.1175/JAS-D-12-0214.1 It costs$35. I’d send it to you except for this:

Found it!
https://depts.washington.edu/amath/old_website/research/articles/Tung/journals/Zhou_and_Tung_2013_solar.pdf

1sky1
June 7, 2014 12:49 pm

The notion that cross-correlation between noisy time-series needs to be “adjusted for autocorrelation” and has confidence limits independent of noise-level is straight out of Lewis Carroll.

Greg Goodman
June 7, 2014 12:56 pm

Willis: “Ah, excellent. The actual analyses. As I said just above, I knew you were a smart guy.
Greg Goodman says:
June 7, 2014 at 2:32 am
http://climategrog.wordpress.com/?attachment_id=956
……”
So smart I’d done it and posted it 9 hours before you told me “directly” to get off my butt and do it.
I’ll take that as an almost apology 😉
Without worrying about the FT of CC for the moment. What information do you think can be derived from cross-correlation. You used it to support your impression that there is no solar signal, so you must expect that something could be there that was not.
I’m guessing you were looking for a peak that is above your 0.2 threshold (but I don’t want to puts words into your mouth, so please correct me if that’s wrong).
How do you interpret ISST vs SSN peaks getting above 0.25 ?

Pamela Gray
June 7, 2014 1:08 pm

At issue here, besides the lack of observation in the temperature anomaly, is the reluctance of solar enthusiasts to first show that there are no other potential drivers that can serve as the energy behind temperature trends.
There is, and one that correlates much better with land temperatures. That would be ocean heat and its teleconnection with atmospheric processes (IE ENSO systems, clouds, large and small varying pressure systems, sudden events that produce aerosols, etc). The mechanism behind this is the heat storing capacity of the oceans along with Earth’s own filtering systems in the atmosphere, a capacity that has more than enough variables attached to it to take a steady state (relatively speaking) source and absorb it in varying amounts, and then belch it back out in varying amounts. I see no need for the Sun to vary in order for that process to work.

LT
June 7, 2014 1:27 pm

Yes it’s very simple, the magnetic field of Jupiter, Saturn, the Sun and Uranus, modulate the magnetic field of the heliosphere and vary the amount of GCR impacts in the upper atmosphere of this planet and all others, and modulate the transparency. The 11 year sunspot cycle is nothing but an effect of the wobble caused by Jupiter alone, the longer term trends are associated with Saturn and Uranus and the way that they are coupled with the Suns magnetic field, and shield us from the galactic plane.
This is all you need to predict the future.
http://cosmicrays.oulu.fi/webform/monitor.gif

June 7, 2014 1:38 pm

From ren on June 7, 2014 at 1:20 pm:

Willis what you think of Dansgaard-Oeschger cycle?

Gee, above he clearly said:

Subject: This post is about the quest for the 11-year solar cycle. It is not about your pet theory about 19.8 year Jupiter/Saturn synoptic cycles. If you wish to write about them, this is not the place. Take it to Tallbloke’s Talkshop, they enjoy discussing those kinds of cycles. Here, I’m looking for the 11-year sunspot cycles in weather data, so let me ask you kindly to restrict your comments to subjects involving those cycles.

The Dansgaard-Oeschger events have an imagined periodicity of 1,470 years, thus do not appear to be the 11-yr sunspot solar cycle.

herkimer
June 7, 2014 1:43 pm

Willis
Since the oceans are 70% of the surface, of course the global temperature and the oceanic SST are very closely correlated … and? What does that have to do with the ~11-year sunspot cycle? What am I missing here?
If it is not the various sun cycles that drive the 60-70 year atmosphere cycle then it is likely the Ocean cycles as Bob Tisdale has cleared shown . I tend to agree with Pamela Gray’,s post . For example the extra cold temperatures in the CET records during past major solar minimums may not be due to solar minimums at all but due to valleys in the North Atlantic SST due to stronger MOC which causes more upwelling of colder water. driven by the oceans conveyor belts . AMO has gone negative now for many months and the past 60-70 year SST pattern may again be repeating it self.

June 7, 2014 1:51 pm

ren says
what do you think of Dansgaard-Oeschger cycle?
henry says
the evidence seems reasonable to me
http://epic.awi.de/13582/1/Bra2005e.pdf
but [I think] you would have to try and link the 1470 year cycle to some special configuration of the solar system,
just like I did with the 87 year Gleiszberg cycle
(predict dead end strop in the middle of the cycle around 2015 or 2016)
Happy hunting!

June 7, 2014 2:00 pm

Dear Willis,
A reader on my infrequently updated blog pointed me out to your post here. Here are my thoughts about it.
You write: “… however, I’m not seeing it. So where can we find this mystery ~11-year cycle?”. So, let me start by referencing earlier work detecting the 11-year solar cycle in the land or sea surface temperature records. The following examples (and quite a few more I didn’t mention) indicate that the peak to peak variations of either SST or land surface temperature are around 0.08 to 0.1°C between solar minimum and solar maximum:
– Douglass and Clader (2002) found a pear to peak variaton of  0.11 ± 0.02K
– White et al. (1997) found a = 0.10 ± 0.02K (looking at eigenmodes in the ocean).
– Shaviv (2005) found 0.09±0.03K (using 300 years of surface data)
Douglass, D. H., and B. D. Clader (2002), Climate sensitivity of the earth to
solar irradiance, Geophys. Res. Lett., 29(16), 1786, doi:10.1029/
2002GL015345.
White, W. B., J. Lean, D. R. Cayan, and M. D. Dettinger (1997), Response of global upper ocean temperature to changing solar irradiance, J. Geo- phys. Res., 102(C2), 3255–3266.
Shaviv, N., On climate response to changes in the cosmic ray flux and radiative budget, Journal of geophysical research, 110(A8), 8105–8105, 2005.
Given these previous detections it is thus worthwhile to ask whether you expect to see a statistically significant signal in the dataset you used. i.e., you should place an upper limit and then compare to previous determinations of about 0.1°C. If the upper limit is bellow this value, then you have something interesting to say, otherwise, the result is isn’t interesting, it just means that the dataset you used doesn’t prove or disprove anything.
When inspecting your fig. 6, the signal you see there does in fact have the right amplitude and phase. So the question is not whether you see a signal or not, it should be whether the signal you see is statistically significant.
To answer this question you have to do some minimal statistical analysis which you haven’t done. For example, you should estimate the probability that the null hypothesis would give the blue line apparent in fig. 6, namely that a large fraction of the points would be as far as they are from the null signal. (e.g., by calculating the chi 2 and the effective number of degrees of freedom). I did this and found that the null hypothesis can be ruled out at better than the 99% confidence level. (and it doesn’t matter if I plotted 1-sigma or 2-sigma error bars on the points).
The two possible answers that you could get are that a) the null hypothesis can be ruled out, implying that this dataset supports the idea that you see a solar signal. b) the null hypothesis cannot be ruled out, which would then just mean that this dataset does not support the idea, but it doesn’t rule it out either. Now, given that there are other data sets that clearly show the solar signal, I couldn’t care less what the answer is.
Next, you don’t see a signal when using the SST from 1870. However, your conclusions don’t consider the following points:
a) The SST over long time scales is very poor, not much signal and a lot of noise. How much of the southern pacific was sampled by boats in the first 50 years of that time interval? In fact, even today it is poorly sampled.
b) You assume that the solar cycle is strictly periodic (say 11 years?) but in fact it isn’t. As a consequence, any analysis such as Fourier transforming, or folding over the period is smeared out from the non-constant period. (You have to fold the data while keeping the right phase within the solar cycle, which I don’t think you did).
c) Like with the previous case, you don’t estimate what is the statistical significance of the null result you find. Are the errors so large that the expected signal drowns in noise?
Last, my biggest grievance about your criticism is that the analysis in the paper you considered was of 3 datasets. You chose only the SST, and disregarded the tide gauge records which shows the solar signal with a very high statistical significance. See http://www.sciencebits.com/calorimeter .Its problem is that it may have some “contaminant” from variations in the amount of ice, but that doesn’t matter if you want to prove that you see a climatic signal over the solar cycle.
You could also ask whether 0.1°C is large or small, and the answer is that because of the large heat capacity of the oceans it corresponds to about 1W/m^2 variations (when averaged over Earth’s surface). So in fact, the small temperature variations observed are at leaf 6 times larger than what the IPCC is willing to admit.

June 7, 2014 2:06 pm

Pamela
“The Earth, with its many ways of storing and belching heat, seems quite capable of hourly, daily, seasonally, and long termally (backdoor alliteration is more fun than plain ol’ alliteration) changing the temperature all by itself-ally.”
The solar variation is so minor that I do the following thought experiment.
I make a chart of TSI versus time.
I label it c02.
I make a chart of temperature versus time
I label it temperature.
Then I imagine what a skeptic would say If I claimed that chart one helped to explain chart two.

June 7, 2014 2:24 pm
milodonharlani
June 7, 2014 2:24 pm

June 7, 2014 at 12:46 pm
Good find. Thanks for your excellent sleuthing, of Jimbo caliber.
Now everyone can have it.
Thanks!

milodonharlani
June 7, 2014 2:35 pm

PS: The references are also useful, whether you’re convinced by their proposed “bottom up” (as opposed to “top down”) mechanism for solar irradiance (or insolation) influence on climate or not.

June 7, 2014 2:44 pm

@nir shaviv
btw
my results [on the Gleiszberg cycle alone] suggest a variation of ca. +0.5 degree C max. in the warming period of 44 years and ca.-0.5 degrees C min in the cooling period.
On average this suggests an average difference of [0.125K] between each of 8 succussive Schwabe solar cycles .[I think] this compares well with your own result.
I am just a small unpaid hobbyist, you know….

Genghis
June 7, 2014 2:45 pm

Willis – “However, I wouldn’t say that the ocean surface temperatures are “controlled almost entirely by windspeed”. Particularly in the tropics, the clouds regulate the amount of energy entering the system. If you get a day with no clouds, SSTs will climb. On the other hand, a cloudy day followed by a clear night will lead to falling SSTs.”
No that is incorrect, and to me very surprising also. I have been measuring it (in the tropics too) and it simply doesn’t work that way. What does get warmer is the layer just below the surface. What happens is that the top warm layer gets thicker during sunny days and thinner during cloudy days and nights, but the surface stays the same temperature as long as there is a warm layer reservoir below it.
I know i sound like a snake oil salesman, but wind speed (via evaporation and conduction) really does control the surface temperature. And it explains everything else too 🙂 Higher wind speeds = lower temperatures as long as there is moisture to evaporate of course, which is why it explains UHI, Climate change, climate warming, cooling etc. Wind is also self regulating, higher temps means increased evaporation which creates lows which increases the wind speed which lowers the surface temperature.
Unless changes in radiation levels can change the wind-evaporation loop changes in radiation levels won’t control the climate. That is also why everyone is searching in vain for correlations with sunspots, CO2, albedo, etc. they don’t exist. But humans are great at spotting patterns : )

milodonharlani
June 7, 2014 2:58 pm

Genghis says:
June 7, 2014 at 2:45 pm
You might be interested in the conclusions of Zhou & Tung (2013).
“4. Conclusions
“We have established statistically the existence of the 11-yr solar cycle signal in temperature throughout the troposphere. There is a robust heating center located over the tropics below the tropopause in all seasons, which is statistically significant. It cannot be interpreted as heating due to ozone absorption of solar UV radiation, since tropospheric ozone concentration is extremely
small. This heating is situated above a minimum in warming over the tropical ocean surface, suggestive of vertical convection caused by surface heating and evaporative feedback (which reduces surface warming). There are two vertical strips of warming outside the edge of the tropics in the troposphere that could be a result of a poleward shift of an expanded Hadley circulation.
The evidence we present here is suggestive of a ‘‘bottom up’’ mechanism for the tropospheric and
surface response similar to that for greenhouse warming, as discussed in Cai and Tung (2012): Most of the solar forcing reaching the surface in the tropics does not go directly into warming the ocean but into evaporating water and heating the upper troposphere through convection and latent heating. From there large-scale transport carries the heat poleward, resulting in a global
warming pattern. Because the tropical ocean is not warmed appreciably, only a small fraction of the heat is transferred into the ocean mixed layer. This may explain why the lag in the surface and tropospheric response is almost nonexistent, smaller than expected based on the thermal inertia of the entire mixed layer, and why the amplitude of the response is close to that estimated at
equilibrium.
“Previously, there have been several general circulation modeling studies with fixed sea surface temperature (SST) (Shindell et al. 1999; Haigh 1996, 1999; Larkin et al. 2000; Matthes et al. 2004; Balachandran et al. 1999) to isolate the ‘‘top down’’ effect. However, given that the visible/near-infrared solar heating in these experiments still penetrates to the surface, evaporates water,
and causes vertical convection, the calculated circulation change could still be, at least partly, from the bottom-up mechanism that we proposed. Since the change in the tropical SST is small in both the observation shown here and in the model of Cai and Tung (2012) where the SST was allowed to vary, fixing the SST in the important tropics in these experiments does not present a condition so different as to prevent the bottom-up mechanism from acting. Therefore, the results from these fixed SST experiments cannot be interpreted as arising only from the top-down mechanism.”
Not sure I consider model tests as experiments, but the approach is better than making a lot of assumptions not in evidence.

Pamela Gray
June 7, 2014 3:11 pm

Nir, you do realize that papers that include “changes in solar irradiance” based on the uncorrected SSN values places you on shaky ground in terms of supporting literature.
A case in point: I wonder if Judith Lean still considers the paper linked below an adequate examination of solar drivers given what she now knows of problems with solar data (IE Leif’s group working on reconciling weighting issue with raw SSN). If my memory serves me, she no longer subscribes to solar reconstructions used in several papers she has co-authored in the distant past. Whether that includes this one I don’t know.

Theodore White
June 7, 2014 3:19 pm

The Sun is about to enter a hibernation phase into solar cycle #25 and that will usher in global cooling, which I have been forecasting for years is coming. It is closer now and will begin officially in December 2017.
As for ENSO, it is driven, like all climate change on Earth, by the Sun and planetary angular relationships to the Sun and Earth.
However, there will be no ENSO this year, next year, or the year after that.
The next ENSO will be a powerful La Nina, that will impact 2020-2022, with the worst winter season in the northern hemisphere in 2021-2022, and it will rival the last brutal winter of 2014 and set new weather records for cold temperatures, heavy snowfall and ice.
In my climate forecast, there will be no ENSO until 2020, and that one will be La Nina – a very strong one at that.
Until 2020, we will see strange cool plumes in worldwide sea surface temperatures; a lack of hurricanes; along with the continued growth and expansion of the Arctic and Antarctic sea ice extents.
This is the trending to Global Cooling, which I have forecasted to begin officially in December 2017 and last approximately 36 years.
ENSO events are solar-planetary forced and occur every 10-11 years. The last ENSO, which I forecasted, was a El Nino in mid-2009 that was followed by a La Nina in 2010-11.
Think of ENSO as climate change in action.
You are seeing what amounts to a large scale variability in the circulatory system, and when you take out ENSO you are removing a climate mechanism where the thermal/kinetic exchange to equilibrium is achieved.
ENSO is externally forced through the polar annular modes/AAM, and ENSO is climate change in action. What confounds the computer modellers about ENSO’s cycle is that the thermodynamic response to perturbation is not linear.
ENSO responds to fluctuations by the external forcing from the Sun.
Understand at the dynamics of ENSO and what forces it.
ENSO is forced by the Sun externally because the strength of the trade winds, that’s Walker Cell dynamics, and the AAM integral come before ENSO SST variation.
Now, the atmosphere is the less energetic body, so by definition there has to be an ‘external’ perturbation present.
Evidence of such Solar forcing exists and the relationship is significant:
Corotating coronal holes of the Sun induce fluctuations of the solar wind speed in the vicinity of the Earth.
These fluctuations of solar wind speed are closely correlated with geomagnetic activity and the resultant geophysical climate and weather effects on Earth.
It is basic to Astrometeorology. That is what I do.
Now, solar wind speeds have been observed and monitored by orbiting Earth satellites since the mid-1960s. The long-term series of solar wind speed clearly reveals enhanced amplitudes at the solar rotation period of 27.3 days and at its harmonics 13.6 and 9.1 days.
The amplitude series are modulated by a quasi-biennial oscillation (QBO) that has a period of 1.75a (that’s 21 months) as bispectral analysis reveals.
A 1.75a QBO component is also present in the equatorial, zonal wind of the stratosphere at 30 hPa, in addition to the well-known QBO component at the period 2.4a (at 29 months.)
The solar wind QBO influences the stratospheric QBO, the global electric circuit, and cloud cover by modulation of ionospheric electric fields, cosmic ray flux and particle precipitation.
And the series of solar wind speed fluctuations are bandpass-filtered at the period 1.75a. The filtered series provide the amplitude of the solar wind QBO as function of time.
The maxima of the solar wind QBO series correlate with those of the ENSO Index. Analysis confirms that the solar wind QBO helps to trigger ENSO activity.
The solar forcing of ENSO is done by changes in meridional flux through the NAM/SAM and that ties directly right back into planetary wave action.
In volume 36, issue 17, of the September 2009 Geophysical Research Letters, Rodrigo Caballero and Bruce T. Anderson state that:
“Stationary planetary waves are excited in the mid-latitudes, propagate equatorward and are absorbed in the subtropics. The impact these waves have on the tropical climate has yet to be fully unraveled.
“Previous work has shown that interannual variability of zonal-mean stationary eddy stress is well correlated with interannual variability in Hadley cell strength. A separate line of research has shown that changes in midlatitude planetary waves local to the Pacific strongly affect ENSO variability.
“Here, we show that the two phenomena are in fact closely connected. Interannual variability of wave activity flux impinging on the subtropical central Pacific affects the local Hadley cell. The associated changes in subtropical subsidence affect the surface pressure field and wind stresses, which in turn affect ENSO.
“As a result, a winter with an anomalously weak Hadley cell tends to be followed a year later by an El Niño event.”
Moreover, there is a link from the Pacific Meridional Mode to ENSO, as Ping Chang and Link Ji from Texas A&M University at College Station, Texas wrote in late 2008:
“The occurrence of a boreal spring phenomenon referred to as the Pacific Meridional Model (MM) is shown to be intimately linked to the development of El Niño–Southern Oscillation (ENSO) in a long simulation of a coupled model.
The MM, characterized by an anomalous north–south SST gradient and anomalous surface circulation in the northeasterly trade regime with maximum variance in boreal spring, is shown to be inherent to thermodynamic ocean–atmosphere coupling in the intertropical convergence zone (ITCZ) latitude, and the MM existence is independent of ENSO.
“The thermodynamic coupling enhances the persistence of the anomalous winds in the deep tropics, forcing energetic equatorially trapped oceanic waves to occur in the central western Pacific, which in turn initiate an ENSO event. The majority of ENSO events in both nature and the coupled model are preceded by MM events.”
Now, the reasons why NOAA/NWS and every other conventional climate center on Earth, along with climatologists and their computer models cannot forecast ENSO; is that their computer models are shit.
ENSO is an *astronomically-caused* climate event.
And clearly the algorithms in their overblown and error-filled computer models are not programmed to understand ENSO.
That is why they cannot forecast it and every single year they come out with forecasts on ENSO and they fail.
They did it last time when I forecasted the 2009-2011 ENSO three years in advance, from 2006.
Rather, what conventional modellers do is that they take an initial condition and then they apply their own perturbation theories to attempt to get a future projection – and those projections are always wrong, wrong, wrong.
In truth, in the real world of climate, ENSO is NOT an internally driven or a chaotic phenomenon.
ENSO is a solar and planetary magnetically-driven event that forces upper stratospheric U-flow/QBO and you can witness the results and impact on the N/S annular modes.
Reports from the CFS project on the 2011 La Nina that I forecasted fell to -4C because those expensive computer models are founded on absolutely useless methods on the given boundary conditions that they use to project from.
It means that they are essentially using a system dynamic that *drives* the system state, rather than the other way around. They have it ass backwards.
For instance, if you subtract ENSO, then you also have to subtract the poleward migration of Hadley cells/expansion of the Ferrel cells seen since solar year 1976.
Now, once you do that, you will lose the 3-4 percent decrease that’s observed in tropical cloud cover. Therefore, you lose essentially all of the warming that has occurred since the 1970s and that relates to about 3.5W/m^2 of loss since 1982.
NOAA/NWS and every other climate forecast center do not successfully produce accurate seasonal forecasts.
Again, that’s because their models are only programmed to the general governing equations that are put into them.
For years now, with all that money they’ve wasted, the computer climate modeling world is a total disaster and they have to know it after busting every season, every year, year in and year out.
Again, there will be no ENSO until 2020. We will see signatures by mid-2019 when things really begin to get interesting, but by 2020 there will a full blown La Nina that will be in force for 2.5 years according to my calculations.
The worst of it will be during the winter of 2021-2022 – a really bad and long winter season followed by a cold, wet spring and cool summer of 2022.
ENSO is climate change in action and that climate change is to GLOBAL COOLING, which officially begins in December 2017. That’s been my forecast and people had better prepare for it too.
~ Theodore White, Astromet

milodonharlani
June 7, 2014 3:51 pm

Willis Eschenbach says:
June 7, 2014 at 3:39 pm
How do you know it’s garbage if you haven’t read it? Ignoring others’ work or dismissing it out of hand doesn’t inspire confidence in your conclusions. Even if you don’t want to consider it, their references include relevant papers.
I don’t think it’s up to me to reproduce their results. It’s your quest to find a signal for the 11-year cycle, not mine. On its face, their methodology looks OK to me.
Courtesy of Kadaka, there’s now a link to Zhou & Tung (2013) in the comments above. I copied their conclusion section.

milodonharlani
June 7, 2014 4:21 pm

I don’t think it’s “true”, but their proposed mechanism makes sense on its face. I brought it to your attention because they find the signal & try to explain it. I don’t rule out reanalysis on its face. I went to the paper they cite, Labitzke et al. (2002), & it looked OK, but I didn’t do any statistical analysis of my own.
I’m OK without an 11 year signal, since the sun’s irradiance & insolation as modulated by earth’s orbital & rotational mechanics (& other terrestrial & ET effects) are IMO clearly implicated in climatic periodicities on the scale of multiple decades, centuries, millennia, myriads, hundreds of thousands, millions, tens of millions, hundreds of millions & billions of years.

ferdberple
June 7, 2014 4:29 pm

Would it be worth renewing the analysis, using cycle-length as the primary criteria?
===========
my point as well. there is no 11 year solar cycle. that is simply a mathematical average.
look for correlation between rate of warming and inverse length of cycle before claiming it doesn’t exist. Otherwise you are simply sailing south from England, claiming the America’s don’t exist, simply because you didn’t find it.

June 7, 2014 4:33 pm

Theodore White says:
June 7, 2014 at 3:19 pm
“The Sun is about to enter a hibernation phase into solar cycle #25 and that will usher in global cooling, which I have been forecasting for years is coming. It is closer now and will begin officially in December 2017.”
I tend to agree with your comment and have been going naked on hurricane insurance in SW Florida since 2009, on the bet the Sun is going into a quiet period, saving a ton of money.
I alluded to this question in a previous solar thread and suggested the Earth acts like a battery, recharging and discharging its absorbed energy. Such a perfect equilibrium from one solar cycle to the next has been enjoyed without noticeable affects, except for current solar cycle 24 in modern times.
Instead of folding, try compressing and stretching like a Slinky the records to correlate each recharge discharge cycle from solar cycle to cycle. Depending on amplitude and duration of any given solar cycle our planet will have a net gain, net neutral, or net loss of energy from one cycle to the next. Maybe my comment yesterday on time lag effects of solar influence nudged Willis Eschenbach also to post an excellent discussion on this matter. I enjoy these discussions. Perhaps an understanding of battery technology recharge discharge cycles, can add to our understanding of how the whole climate of the planet works.

ferdberple
June 7, 2014 4:34 pm

I’m OK without an 11 year signal
=========
So am I, because there is no 11 year solar cycle. The 11 year cycle is a mathematical average of the true solar cycle. It is an imaginary construct. It does not exist. Read Briggs about using averages for anything. It is garbage in, garbage out.

Editor
June 7, 2014 4:37 pm

Willis, you say “However, none of that matters. Why not? Well, because the claimed effect disappears when we use the full SST and sunspot datasets.“. But then you say “This highlights a huge recurring problem with analyzing natural datasets and looking for regular cycles. Regular cycles which are apparently real appear, last for a half century or even a century, and then disappear for a century …“.
Given that Earth’s climate system is complex, coupled and non-linear [as per the latter part of your statement above], and given that any effect of the “11-year” solar cycle must if it exists be weak and/or inconsistent because otherwise it would have been quite easily found already, it follows that your argument based on it not being visible in the full SST record is invalid. ie, if it does exist then the full SST record is not the place to look.
So where should one look? Other commenters have suggestions, which I haven’t yet checked, but I would suggest looking in selected regional data. Maybe rainfall or diurnal temperature range or whatever data does exist, in various individual locations. Maybe some commenters here have already found something valuable – I confess I haven’t followed them all up.
NB. I’m not saying that the sunspot signal exists, just that if you are serious about looking for it then instead of looking in the places (eg. full SST) where you have already failed to find it, it would be a good idea to start looking in other places. Please understand that this is not meant as a criticism but as a helpful comment.

June 7, 2014 5:09 pm

Greg Goodman says:
June 7, 2014 at 8:09 am
——————————–
“I suspect this may be correct but I’ve yet to see the “proof”.”
Greg, happy to oblige –
http://i42.tinypic.com/2h6rsoz.jpg
The best way to understand is to build and run the experiment for yourself. Start with 40C water samples under the strong and weak LWIR sources. You should notice little or no divergence in the cooling rate of the water samples. Now repeat the experiment but float a square of LDPE film (cling wrap) onto the surface of each sample. This allows conductive and radiative cooling but prevents evaporation. You should now record a distinct divergence in the cooling rate of the samples.
I have run a number of these type of experiments since 2011. I can assure you that LWIR does not effect liquid water that is free to evaporatively cool in the same manner as it would a “near blackbody”
Posts by others who have also taken in situ IR measurements of the ocean also support these results – Genghis says: June 7, 2014 at 10:22 am

David Riser
June 7, 2014 5:11 pm

Yo Michael, betting on the weather is always a bad idea….

June 7, 2014 5:22 pm

The Earth rotating on its axis at about 1000 MPH while orbiting the Sun at around 67,000 MPH and circling the center of our Milky Way galaxy at about 514,000 MPH while taking about 230 million years to make one complete orbit around the center, is it any wonder why the climate of our planet is so complex. It’s enough to make your head spin. But factoring all this out, our Sun is still the main driver of Climate Change.

Pamela Gray
June 7, 2014 5:30 pm

milodonharlani says:
June 7, 2014 at 4:21 pm…
“I’m OK without an 11 year signal, since the sun’s irradiance & insolation as modulated by earth’s orbital & rotational mechanics (& other terrestrial & ET effects) are IMO clearly implicated in climatic periodicities on the scale of multiple decades, centuries, millennia, myriads, hundreds of thousands, millions, tens of millions, hundreds of millions & billions of years.”
In other words, natural intrinsic Earth factors modulate solar irradiance/insolation, thus drive temperature trends. So we are back to the null hypothesis. And what a strong one it is too.

Gary Pearse
June 7, 2014 5:32 pm

richard verney says:
June 7, 2014 at 12:49 am
June 6, 2014 at 11:51 pm
////////////////////////////////////////////////////
”We hold similar views, and…
divorced layer of spray and spume in these (GP: avg over the oceans) conditions would almost fully absorb DWLWIR and as it does so, it would heat and would be carried upwards in the atmosphere initally warming the atmosphere and keeping the DWLWIR away from the ocean below.”
Well now, this is a fine piece of thinking. The very multiplier of heating used by CAGW proponents (water vapor) that is going to destroy the planet actually serves as a ”sunscreen” over the oceans (and very likely over the humid tropics). The mysterious 31C maximum SST temp would seem to be explainable with this effect. The hotter it gets, the more sunscreen that’s added until a maximum SST is reached.

dp
June 7, 2014 5:54 pm

Greg: Let me know when you’ve read what I’ve posted so far.

You need to describe the natural processes that create the charts you’ve created mathematically. All you’ve presented so far is a weak correlation and correlation is worth only the paper it is printed on. I find your argument to be weak and you to be annoying. The old “See? It lines up” argument isn’t going to do it. Were I you I’d start looking closely at chronobiology as a first step.

Frederick Michael
June 7, 2014 5:58 pm

Let me emphasize something I said earlier that seems not to have caught on. If the solar effect drives dT/dt (that is, T moves with the integral of sunspots or whatever) then the response may be WAY too slow to see any kind of 1 year pattern. What you may see is a dip in T if we get a few weak solar cycles in a row.
Testing this would require good data going back pretty far. Willis’s figure 1 isn’t quite long enough, though it shows one slightly weak set around 1880-1930. The current cycle may end up weaker than any of those. The test is trivial though — you could do it in Excel. The solution to the differential equation is just an exponential smoothing function (assuming a liner relation between heat outflow and T — which holds over the range of T we’re dealing with).
However, let me add another twist — if solar cycles drive dT/dt then dT/dt might be a function of the INVERSE of the solar driver (especially if it’s a magnetic effect, not direct solar energy). This would amplify the distinction between a weak solar cycle and a very weak one (or one with a long minimum — like we just had). Side note — this might explain why solar cycle length seems to matter. However, this would work better if solar cycles were measured peak-to-peak instead of minimum-to-minimum — which tends to split the long minimums in two.
One last twist — if we let dT/dt move by the inverse of some solar driver that driver can’t be something that goes to zero when sunspots cease; it’s more likely something like the F10.7 flux. Unfortunately, data on that is far less extensive. Still, some kind of proxy function could be built to approximate F10.7 flux as a function of sunspots.
Willis is right to want people to do more than just chatter about their hypotheses (which I have just done, AGAIN). I’m ridiculously busy but the analysis isn’t hard. If anyone thinks they can get adequate data going back a few centuries, I’d be happy to collaborate.

Frederick Michael
June 7, 2014 5:59 pm

Oops. I meant 11 year pattern, not 1.

Pamela Gray
June 7, 2014 6:07 pm

It would stand to reason that the weaker the solar driver be, the stronger and more visible the amplifier must be. So even on long time scales, the amplifier should be visible if it is driving trends. Therefore the amplifier should be easily located and will correlate to a very weak solar signal.
Think about this: The weaker your solar signals are, the harder it will be to prove your solar hypothesis without a really big and easy to find amplifier. And if you espouse a series of weak amplifiers I fear we are being asked to find nothing more than dust fairies, and invisible ones at that.

Paul Westhaver
June 7, 2014 6:44 pm

Day versus night temperatures vary up to 30 to as high as 40C on earth. That means that the surface temperature of the earth changes, let’s say 30C, in 24 hours… all the time. +/- 1C. Night is cold. Day is warm. We have strong evidence of the gain and time constant of the sun’s radiative effect on earth. That is all as a result of the sun being on or off so to speak.
The so-called solar constant varies 0.2% over an 11 year cycle.
So called global warming yields a signal of 0.1 degree per year… ish so they say.
It is obvious to me that the sun has a direct effect on the earth. It is also obvious to me that variations in the sun radiance must therefore effect the earth.
Trouble is, the earth spins and there are clouds. The spinning earth is pretty constant. Seems to me that perturbations in clouds and the solar radiance may yield an effect but really, how can you see that effect when it is lost in the noise created by the day-night cycles not to mention the seasonal cycle?
What is the earths daily average temperature on the surface and what is the +/- error associated with that calculation? Anyone?
It is the sun stupid. However, measurement systems are still far to primitive to resolve the signals to any degree of precision sufficient to separate periodic radiance variations from simple day to day variations.

June 7, 2014 6:45 pm

Pamela Gray says:
June 7, 2014 at 6:07 pm
———————————-
“It would stand to reason that the weaker the solar driver be, the stronger and more visible the amplifier must be.”
This is not necessarily so. We are only looking for 0.8C in 150 years. A process of accumulation not amplification can cause this.
It is the higher solar radiation frequencies that vary most between solar cycles. It is these frequencies that penetrate deepest into the oceans. (UV-A still having the power of 10 m/2 at 50m depth.) Penetration exceeds the diurnal overturning layer, so energy can accumulate.
However we do not have sufficiently accurate SST records for 150 years to quantify the real world effect, but the mechanism is easily demonstrated by empirical experiment.
If you falsely treat the oceans as a “near blackbody” not a selective surface and only look at total TSI variation, not individual frequencies then you will end up wasting time looking for instantaneous SST response to 0.1% TSI variation, which as I indicated at the start of the thread, is a dead end.

Genghis
June 7, 2014 7:21 pm

Paul Westhaver says:
June 7, 2014 at 6:44 pm
“Day versus night temperatures vary up to 30 to as high as 40C on earth. ”
Paul, according to my measurements, day vs night, cloudy or clear, surface ocean temperature measurements in the sub and tropical oceans do not vary at all.
If the radiative difference of over 7000 watts in a 24 hour period can’t produce a temperature change, what difference can a fraction of a watt make?
Above a set temperature point evaporation totally dominates in the energy budget. All of the energy budgets show that evaporation is the dominant force.

June 7, 2014 7:22 pm

Antarctica is always frozen all year round because the Southern Hemisphere is furthest away from the Sun during its winter solstice, as opposed to the Artic which is closet to the Sun during its winter solstice and accumulating a limited amount of ice during the Earth’s yearly orbit. If this correct TSI has a distinct measurable effect on one pole versus the other. Unless the Sun has virtually no effect whatsoever because it’s a benign star.

tobyglyn
June 7, 2014 8:46 pm

Any comments regarding Nir Shaviv’s ?
Nir Shaviv says:
June 7, 2014 at 2:00 pm

Paul Westhaver
June 7, 2014 9:11 pm

Geghis,,
I asked “What is the earths daily average temperature on the surface and what is the +/- error associated with that calculation? Anyone?”
And you kindly responded. Thanks.
I was thinking of surface air temp not water below the surface even if it is 0.01mm. I wasn’t specific. My apologies.
Evaporation is the dominant energy sink in the energy budget. Agreed. The evaporant, water, does also change in temp as well transposition in phase. When I hear about global warming, I think about the air temperature increasing. The 0.1C delta I referred to was the surface air temp increase.
But more to my point, what is the ERROR or uncertainty in the so-called average air temperature of the earth?

RACookPE1978
Editor
June 7, 2014 9:23 pm

Willis:
you are on the right track, but left out a few other very, very important differences between the total Antarctic ice and the total Arctic ice. Let us skip Greenland for a bit.
The Arctic sea ice is surrounded by what is essentially tundra – wet, muddy, flat LAND at a rough circle at about latitude 70-72 south. In the arctic summer, the land has no ice on it at all. The Arctic sea ice drops from a March-April high of about 14 Mkm^2 to a September low of 6-7 Mkm^2 supposedly based on the 1970 data, down towards today’s average 4 Mkm^2 sea ice extents. Sea ice extents have twice gone to right at 3 Mkm^2 in 2007 and 2012.
At the earth’s radius, assuming a beanie cap over the pole – which is almost right.,
1 Mkm^2 of sea ice covers the north pole down to 85 degrees.
2 Mkm^2 of sea ice covers the north pole to 83 degrees.
3 Mkm^2 of sea ice covers the north pole down to 81 degrees.
4 Mkm^2 covers the pole down to 80 north latitude.
Thus, at today’s minimum sea ice extents in mid-September, the NOONDAY sun is only 8 – 10 degrees above the horizon! It is trying to penetrate an air mass between 34 and 16 atmospheres thick, to hit a piece of ocean whose solar elevation angle has an effective albedo on open water and average wind speeds of only 0.20 to 0.34.
The Antarctic sea ice extents surrounds the 14 Mkm^2 continental land mass + the 3.5 Mkm^2 permanent shelf ice. The minimum Antarctic sea ice extents of 3 – 4 Mkm62 surrounds that 17.5 Mkm^2, so even at its LOWEST sea ice extents, the MINIMUM effective Antarctic sea ice represents an area not of 3 – 4 Mkm^2, but 21 to 22 Mkm^2. At its MINIMUM Antarctic sea ice extents in February-March, the edge of the Antarctic sea is is not at 83 or 85 south latitude, but at 70 south latitude! At its sea ice extents maximum – now setting new records the past few years at 19.5 Mkm^2 – the total Antarctic ice cap goes fro the south pole all the way up to latitude 59 south.
And it is expanding steadily even further fro the south pole every year, every month. May 8 this year? Just that 1.6 Mkm^2 “excess” Antarctic sea ice “excess” was 97% the size of Greenland. Not as thick of course, but even closer to the equator than Greenland’s ice.
Worse, the Arctic sea ice has roughly 50% “old ice” each year, and that dirty old ice has a very low albedo measured by Curry in the SHEBA ice camps as low as 0.38 – 0.40. Average minimum sea ice albedo in the Arctic i June and July each year is not a pristine 0.93 or 0.90, but only 0.45. That Antarctic sea ice IS however almost all fresh frozen sea ice with very, very little dirt and carbon black on it ever.
Thus, the edge of the Antarctic sea ice is not only cleaner and is reflecting from a solar elevation angle 3 – 5 time higher than the Arctic sun, it is receiving five times as much net solar radiation at sea level on those same days in late August and mid-September.
Net? the Antarctic sea ice edge receives more sunlight seven months of the year, the little bit of Arctic sea ice receives more sunlight only 5 months of the year.

June 7, 2014 9:41 pm

Willis Eschenbach says:
June 7, 2014 at 8:57 pm
“Thanks, Michael. Unfortunately, while it’s an interesting theory … I’m afraid it’s not correct.”
Thanks for the response Willis. I’m aware there is land mass below the Antarctic ice sheet as opposed to water under the Artic ice sheet. My point is the un-even solar heating of the polar regions due to the distance from the Sun during their respective winter seasons. Although it’s only a difference of 3 million miles respectively, over billions of years it makes a big difference.
http://www.earthonlinemedia.com/ebooks/tpe_3e/earth_system/elliptical_orbit.jpg

Greg Goodman
June 7, 2014 10:05 pm

June 7, 2014 at 5:09 pm
Greg Goodman says:
June 7, 2014 at 8:09 am
——————————–
“I suspect this may be correct but I’ve yet to see the “proof”.”
Greg, happy to oblige –
http://i42.tinypic.com/2h6rsoz.jpg
The best way to understand is to build and run the experiment for yourself……
I have run a number of these type of experiments since 2011. I can assure you that…..
=============
” I can assure you that…..” , LOL.
Thanks Konrad. So the “proof” you claim, as I suspected, does not exist. Thanks for the clarification.
I still _suspect_ there may be some truth in the idea, which is why I’d like to see some proof. What I don’t understand is why after 30y of intense investment in research no one in climatology seems to have tested this most basic physical question, physically.

Ed, Mr. Jones
June 7, 2014 10:17 pm

Willis,
You said, above: “Why would the climate respond to a weak 22-year signal but not to a strong 11-year signal?”
Maybe “strength” and “Weakness” are habitual conventions/perceptions being applied? (How do I say this?) Can we rule in that the ‘strong’ is in fact strong, and the ‘weak’ is in fact weak? We could easily have evolved to call what we know as “Cats” Dogs, and vice-versa.
Could the Strength lie in period/duration rather than amplitude? Could there be resonance characteristics?
I suppose there’s just not enough data, and when there is enough data a lot of currently popular notions will seem quaintly absurd.
Maybe I’m a Doofus.

June 7, 2014 10:28 pm

I found this image for a clearer understanding of un-even solar gain at polar regions;

June 7, 2014 10:29 pm

Tried to embed this image but failed in my previous post;
http://www.emeraldecocity.com/Pictures/Why%20we%20have%20summer%20and%20winter.jpg

June 7, 2014 10:34 pm

From michaelwiseguy on June 7, 2014 at 9:41 pm:

(…) My point is the un-even solar heating of the polar regions due to the distance from the Sun during their respective winter seasons. Although it’s only a difference of 3 million miles respectively, over billions of years it makes a big difference.

Over billions of years the Sun has brightened, the planetary orbits have shifted while the asteroid belts and even moons formed and grew, we might even have had a rogue planet or two pass through the system, or be captured, or collide.
Then there’s that stupid continental drift, where our current polar regions aren’t the ones we had before, it was ocean at both ends.
Projecting back the possible effects of our current Sol-Terra distance variations to billions of years ago, or just millions, might no be that wise, guy.

Greg Goodman
June 7, 2014 10:35 pm

W: “And even if that were not true, you still only get 163 years of “data” using your 2% solution … and from that you are diagnosing a 170-year signal. Does the name “Nyquist” ring a bell?”
Nyquist says you need at least two samples per cycle. How many monthly samples do you think there are in 163 years? This has nothing to do with Nyquist.
You quoted my words , then ignored them and reinterpreted. Now you re-quote me and chop out even more of what I said in an attempt to refute my objection. At least try to be honest, rather that twisting and misquoting.
Nowhere did I say there was a 170 “cycle” , in fact I explicitly drew attention to the length of the data in relation to that peak and explicitly said there was no grounds to interpret it as being cyclically repetitive.
For the third time, here is what you are choosing to ignore in order to criticise me for you misinterpretation of what you think I said:
“It should also be noted that is a clear anti-correlation with period of about 140 years and a lag of half that. That is a period of time, there is not enough data to suggest this is periodic as in cyclically repetitive.”
Now please stop pointless arguments based on misquoting and misinterpreting and get back to looking at the data.

June 7, 2014 10:42 pm

June 7, 2014 at 10:34 pm
“Projecting back the possible effects of our current Sol-Terra distance variations to billions of years ago, or just millions, might no be that wise, guy.”
With all that going on, how can anyone think there should be no significant climate change except what man makes?

Peter Sable
June 7, 2014 10:43 pm

After numerous of these types of discussions, I’ve come to the conclusions that:
(1) Statisticians should not do signal analysis. They make so many basic mistakes it’s just painful to anyone versed in the art.
(2) If you are using “R”, you are probably a statistician. See conclusion #1.
So my immediate filter is “if it’s being modeled in “R”, it’s probably wrong”

Greg Goodman
June 7, 2014 10:48 pm

You chose to use cross-correlation of hadISST in attacking Shaviv 2008, so I’ll repeat the question you forgot to answer relating to the key point you are trying to make in the article:
Without worrying about the FT of CC for the moment. What information do you think can be derived from cross-correlation. You used it to support your impression that there is no solar signal, so you must expect that something could be there that was not.
I’m guessing you were looking for a peak that is above your 0.2 threshold (but I don’t want to puts words into your mouth, so please correct me if that’s wrong).
How do you interpret ISST vs SSN peaks getting above 0.25 ?
http://climategrog.wordpress.com/?attachment_id=959

Peter Sable
June 7, 2014 10:59 pm

“http://climategrog.wordpress.com/?attachment_id=956”
Greg, where’s the source code? You can mess up the data so badly in so many ways (like decimating with a boxcar average filter like in the original article). We need to review the source code. (I note that your periodiogram of SSN matches mine though, so it’s probably right, or at least as wrong as mine).
My basic checklist for any signal analysis.
(1) was decimation done? Why did you bother introducing more error by decimation? FFTs on modern computers are very fast and there’s not enough reliable monthly history of any meteorological data set to make a modern computer even hiccup. If you have data sets with mismatched periods the proper procedure is to interpolate, not decimate. As a rule of thumb I always interpolate by 4x or 8x just to avoid any computation-induced issues. If you need to decimate please use a proper filter, not a boxcar average. If you want to decimate for display purposes make it the very last operation.
(2) was proper windowing done? You’ll spread sinx/x noise all over your FFT if you don’t.
(3) was the data zero-padded for better inspection of low frequency components? Note that you need about 8 cycles to get any decent quality low frequency information – the error is 1/period, and 1/8 means 12.5% error. For the ~300 years of sunspot numbers any supposed cycle any period discovered that’s > 40 years is highly suspect. It’s probably just noise. It’s not correlatable to anything else.
(4) was the data filtered before FFT to avoid aliasing?
(5) was any filtering done with a reasonable filter? e.g. a hamming filter or other linear-phase filter. averaging is wrong wrong wrong, and a clear sign you don’t know what you’re doing.
The original article that was reviewed failed every item in this checklist.

Peter Sable
June 7, 2014 11:01 pm

Basic signal analysis – based hypothesis: If the oceans are a low pass filter, it’s entirely possible that the sun affects ocean temperature, but you won’t see it in an 11 year cycle because that signal is filtered away. Alas, we don’t have enough data to see cycles much longer than 35-40 years. Time to stop looking for patterns in the noise…

June 7, 2014 11:11 pm

Its funny willis.
These guys have this theory. And some like greg actually know a couple bits of math.
And you make a simple challenge.
1. show me the data set
2. show me the method
that would prove their case.
Of course, they point you at papers ( not data) and they blather on about methods ( usually with no code)
and they have all manner of wild goose chases to send YOU on to prove THEIR idea.
And when you fail to prove their idea, they blather on some more about how you should have done it
and where the effect might lie.
there be unicorns
you just cant find any.

RH
June 7, 2014 11:20 pm

Woodfortrees provides an audio representation of their data. When I load the audio into Audacity, and plot the spectrum using Audacity’s built in spectrum analyzer, there is always a nice spike at 11 years. Coincidence?

Peter Sable
June 7, 2014 11:24 pm

“if a system responds strongly to changes in input on a day-to-day basis, as the SST does,”
Okay, I’ll just change it to a multi-bandpass filter 🙂 Sure the surface temperature changes daily, but the depths do not, and mixing between the two is going to be slower than daily The depths likely feedback enough to stop an 11 year cycle from being seen on the surface.
Frankly any hypothesis is possible that’s not obviously wrong – we don’t have enough data…

Peter Sable
June 7, 2014 11:45 pm

“http://climategrog.wordpress.com/?attachment_id=956”
Greg, now that I look a bit closer, it looks like you didn’t window – suspiciously looks like sinx/x noise in there…

John Reistroffer
June 7, 2014 11:58 pm

There are several people who claim to have seen a correlation between the duration of the “11 year” cycle the amplitude and the effect of warming. Shorter the length “11 year” cycles, have stronger amplitudes with greater effect on warming.
Some references:
E Friis-Christensen, K Lassen – Science, 1991
H Svensmark – 1998
SK Solanki, NA Krivova, M Schussler… – ASTRONOMY AND …, 2002
T Landscheidt – The Solar Cycle and Terrestrial Climate, Solar …, 2000

June 8, 2014 12:10 am

You’re such a trooper Willis. I hope you decide to revisit this topic again in a future post. “Using the Oceans as a Calorimeter to Quantify the Solar Radiative Forcing”, or seeing the oceans as a capacitor like device or a simple power storage battery whatever. With over 332,519,000 cubic miles of water on the planet that’s about 352,670,000,000,000,000,000 gallons, it’s not an easy task to find that 11 year solar cycle signal in all that wet water.
Perhaps this would be a good time to revisit this previous thread of yours;
Ocean Temperature And Heat Content
Posted on February 25, 2013 by Willis Eschenbach
“That tells me that it takes about a thousand zeta-joules to raise the upper ocean temperature by 1°C.”

June 8, 2014 12:14 am
June 8, 2014 12:24 am

“However, I think at this point I’ve heard every conceivable excuse for not being able to find the 11-year signal …”
I think it highlights what one gets when one starts to look at data with no real “idea” of how the system works.
Its why I ask the question “why does anyone think the 11 year cycle show show up?”
If you start with a notion that “its the sun stupid” then you cant help but continue to insist that other people are looking in the wrong way or looking at the wrong thing
If you start with a notion that ‘damn, its really complicated, theres the sun and clouds and oceans
and GHGS, and …. and its all inter connected” then you wouldnt be shocked to find out that tiny
variations in the sun had no discernable effect” you conclude.. hey this thing is more complicated than a circuit or a steam engine.

June 8, 2014 12:44 am

Greg Goodman says:
June 7, 2014 at 10:05 pm
————————————
Proof does not exist? I have been running these experiments since 2011 –
http://i47.tinypic.com/694203.jpg
I am not lying to you. I am not a climastrologist. I work in engineering.
Just conduct the experiment as shown. Remember –
“Tell me I’ll forget. Show me I’ll understand. Let me do it I will KNOW.”
Type is cheap. Do the experiments and you will know. I have little interest in just publishing my results. I am more interested in others replicating experiments.
I consider the Internet to be a permanent record. If I present an empirical experiment, I have built it, I have run it. No if, no but , no maybe. I am not a climastrologist. I do not lie.
“What I don’t understand is why after 30y of intense investment in research no one in climatology seems to have tested this most basic physical question, physically”
Do the experiment and you will know why 😉

Alex
June 8, 2014 1:48 am

Nothing more to learn from this thread. I am leaving it to allow Willis and Mosh to tongue kiss. That’s not why I come WUWT.

richard verney
June 8, 2014 2:13 am

June 7, 2014 at 6:24 am
richard verney says:
June 7, 2014 at 12:49 am
//////////////////////////////////////////
Interesting. I agree that it appears that the atmosphere serves to cool the planet.
My point about wind swept spray and spume is this:
In Willis’ article ‘Radiating the Oceans’ Willis essentially cited the gross energy transfer budget, then said that equation balances, and then said if we remove DWLWIR, from such budget, the oceans would freeze, then said we know that the oceans are not frozen, QED the gross energy flow budget must be correct. That proves nothing, since the net energy flow budget also balances and it does this without DWLWIR. The fact that either or indeed both equations balances proves nothing.
So my point is, does all the claimed DWLWIR actually enter the ocean, because even if only 99% of it entered the ocean, over time (and we are taliking from the dawn of time that Earth first acquired oceans), the oceans would freeze if the gross flow energy budget governed and if only 99% of the claimed DWLWIR actually entered the oceans.
You correctly observed that some of the LWIR absorbed in the wind swept spray and spume would be re-radiated downwards towards the ocean. I agree, but of course, it is only some of the DWLWIR (re-radiation is omni-directional with say only (somewhat less than) about 50% being re-radiated in a generally downward direction). As we talk, in broad terms, about 1/3rd of the oceans are experiencing circa BF2, 1/3rd BF 4 to 5, and 1/3rd BF 6 to 8. In open ocean, it is rare to see less than BF2, unless in the doldrums. On the other hand, there will be large areas where severe storms are ravaging. Some of the wind swept spray and spume will find its way back into the ocean (along with any energy DWLWIR that it may have absorbed), but much of it won’t since it will evaporate or rise fuelling the cloudy conditions above (and with it latent heat changes will happen as phase changes take place).
So I am posturing that in the real world conditions that we see on planet Earth, not all the DWLWIR would get entrained in the oceans. Even if it is only few percent of DWLWIR that is essentially shielded from the oceans by the divorced layer of wind swept spray and spume which ravages above a not insignificant size of ocean, this has significant impacts on those who rely upon a gross flow energy budget for explaining why the oceans do not freeze.
Currents and wind play a large role in explaining ocean temperature profiles. Of course, wind also helps drives evaporation. In one of Willis’ arcticles on ARGO, he suggested that evaporation explained why the ARGO temperature data was capped at 30degC. Whilst evaporation does play a role, I suggested to him that it is not the sole reason since there are large ocean areas with higher than 30deg C temperatures commonly recorded (eg Gulf of Mexico, Red Sea, South China Sea, parts of the Indian Ocean, the ocean off the West coast of Arrica etc), I suggested that it is currents and wind which re-distribute temperatures from the equitorial and tropical seas polewards (and ocean overturning that helps distribute SWIR absorbed in the first 10 metres downward to depth) that is the main reason why the bulk ocean surface temperature is capped at 30degC.
I have seen your experiments, the results of which are extremely interesting, and could well be of signiificance. I have often thought that these experiments should be scaled up and replicated in laboratory conditions. There are plenty of large scale ship model tanks that could be used so that one has a large volume of water and a large surface area. It must be possible to rig something up so that the effect of the relevant LWIR bandwidth on water can be tested.
I have always been bemused why climate scientists do not attempt to experiment to test some of the theories upon which they rely. I don’t count computer modelling testing. That and the poor quality of data upon which they rely without questioning, and which data they frequently over stretch, is a poor testament of the quality and rigour of this particular head of science.

Greg Goodman
June 8, 2014 2:15 am

Peter Sable says:
“http://climategrog.wordpress.com/?attachment_id=956″
Greg, now that I look a bit closer, it looks like you didn’t window – suspiciously looks like sinx/x noise in there…
====
Yes, I know what you mean, that’s why I commented on it being odd. Both datasets have a long term rise, this is what causes the roughly triangular long term from in the cross-correlation, although this does reverse at the ends.
IIRC I used an extended cosine window on that plot. This generally provides better resolution but does need essentially flat data. Of course if you use something like a Kaiser-Bessel window in that which is quite heavy damping effect you are distorting the data to suppress a long term correlation that is real. Swings and roundabouts.
Here’s a quick lash-up comparing ISST vs SSN to ICOADS vs SSN , using KB windowing
http://tinypic.com/view.php?pic=nmzxo9&s=8#.U5QiwaKBwrQ
(To address Willis’ 2% criticism, both series are cropped at 1880, icoads is continuous with 20% cutoff in that range.)
This time plotted in frequency and amplitude scaled by 1/f as a concession red-noise arguments.
The low frequency peak has been bent down to 114y in period. Even with the 1/f scaling it is a significant part of the spectrum. Looking at the CC function the negative correlations are separated by about 140y, without being distorted.
http://climategrog.wordpress.com/?attachment_id=958
It is interesting that the ISST “reanalysis” data seems to almost completely remove the 11.4 year peak in ICOADS but correlates much more strongly with SSN at 10.2 and 5.25 years.
I don’t know the mojo that is used in deriving ISST so I can’t say which is better, maybe ISST is resolving some detail better than unprocessed ICOADS. I am a little suspicious of the how featureless its is around the zero lag tough:
http://climategrog.wordpress.com/?attachment_id=959

Greg Goodman
June 8, 2014 2:34 am

Willis: “I’m interested in evidence, not some hypothetical possibility of the oceans acting as a multi-bandpass future. ”
You are interested in evidence that supports your conclusions, anything else, not so much.
http://wattsupwiththat.com/2014/06/06/sunspots-and-sea-surface-temperature/#comment-1656878
Even when it’s basically what you chose to do yourself.
Is a correlation of 0.25 at 10y and 22y less important now than when wrote the article?

June 8, 2014 2:38 am

From Willis Eschenbach on June 8, 2014 at 12:09 am:

It’s absolutely possible that all of the molecules in my coffee cup happen to be moving upwards at the same time, too, so all my coffee might spontaneously jump out of my cup … but that doesn’t make it worth discussing.

For a straight-walled cup that’s 3″ deep and filled to the brim, the average kinetic energy per molecule would need be enough for a ballistic trajectory at least 1.5″ high, the average height to clear the edge.
And it would be quite a sight to see the coffee flash transform into a supercold solid powder, with much latent energy irretrievably radiated away, before crashing back down into the cup as a cooler liquid with perhaps some ice as the kinetic energy is reclaimed.
In another thought model, there would have to be enough thermal energy in the coffee to expand a (perfectly insulated) hot air balloon from room temperature to generate enough lift to suspend that mass of coffee.
I don’t see it happening. Unless you drink your coffee far hotter than I do. And far stronger too, possibly.

June 8, 2014 3:15 am

Dear Willis,
“Mmmm … were I in your shoes, I don’t think I’d advertise that attitude. Sounds a whole lot like “My mind is made up, don’t bother me with facts”
Willis, when studying a dataset and looking for an effect (such as a solar/climate link), you can either detect at some significance or place an upper limit at some significance. If however the upper limit is above the signal I expect, it means that the dataset is irrelevant for proving or disproving the effect, which implies that “I couldn’t care less”, caring more about it would be a waist of time. This wouldn’t be the case if the upper limit was below the signal I expect (it would make me worry), or the detection at a high statistical significance (and it would make me happy).
Tide gauge records:
It should be apparent from reading Shaviv 2008 that the tide gauge data is the dataset having the solar signal detected with the highest statistical significance, so ignoring it is kind of missing the whole point of Shaviv 2008. Namely, the tide gauges prove that the there is a solar signal and you can consistently see it in the noisier SST and even noisier heat content.
As for the tide gauge data record itself, I didn’t collect it so no point in republishing it (it is not my habit of publishing other people’s stuff, especially after having being threatened once with a lawsuit). I downloaded it from a repository available to anyone with an internet connection. The stations I used are those chosen by Holgate (so that I cannot be accused in cherry picking). The only difference (and it is clearly explained in the the paper) is that I averaged the derivatives of the stations and not differentiated the average to get the sea level change rate. This way I avoid the spurious jumps that you get in years with stations added and removed, which otherwise contributes a lot of noise (and which people didn’t realize and therefore remove before). Anyone can redo what I did.
Folding the data:
If you properly folded the data, than my apologies. I assumed you didn’t because the folded graphs have “years” and not a phase for their x-axis (which is still problematic towards the end of the cycles, besides being misleading).
Cheers
Nir

June 8, 2014 3:15 am

Alex said on June 8, 2014 at 1:48 am:

Nothing more to learn from this thread. I am leaving it to allow Willis and Mosh to tongue kiss. That’s not why I come WUWT.

Meh. It’s Willis talking math, and also cycles and somehow the solar system. Thus a practical guarantee the comments will be infested by Goodman holding court, trying to impress with his madz math skillz, seeing how many he can direct to his site to be flabbergasted by the blabbergasting, as he ruthlessly attacks all perceived inferiors with neither mercy nor understandable explanations.
When Goodman sets up a meeting of his Superior Geniuses Only club and hangs out the “No Ignorant Morons” sign, I know the chances of learning anything in the Comments is vanishingly small. A quick glance through is all they’re worth, and likely that will be wasted effort.

richard verney
June 8, 2014 3:23 am

Gary Pearse says:
June 7, 2014 at 5:32 pm
/////////////////////////////
Garry
What Konrad and I were discussing is whether DWLWIR effectively heats the oceans. I don’t want to discuss that at depth since it is not directly germane to Willis’ present article.
That said, the issue is whether the heating of the oceans is entirely by solar, or does DWLWIR play a significant role? Konrad has performed an experiment that suggests that DWLWIR does not effectively heat the oceans. I was considering the position from a different perspective, namely real world conditions that are encountered every day over the oceans.
The issue is what is going on in say the 10metre atmosphere layer above the ocean, the pico layer of the ocean, the first few micron layer of the ocean, the first few millimetre layer,and say the first 10 metres of the ocean. this raises the issue is a photon just a photon, or does the place where the photon is absorbed play a material role.
In general according to the K&T energy budget cartoon, DWLWIR ad approximately twice the energy of solar. Given the absorption charactericis of SWIR in water (and bear in mind that sea water is not pure water), Solar IR is being absorbed in a volume represented by about the first 20 metres of water (some is absorbed at depths well below that). Given the absorption characteistics of LWIR in water, DWLWIR is absorbed within 10 microns, with 60% of all DWLWIR absorbed fully within just 4 microns.
Thus in broad terms as much energy that solar imparts into a volume of 20 metres of water is through DWLWIR being absorbed in just 4 microns (ie, 60% of all DWLWIR is fully absorbed in 4 microns and DWLWIR has twice as much energy as Solar SWIR – 60% of double is aprroximately the same in broad terms),
Solar SWIR does not boil away the oceans because all the energy is absorbed within a large volume, ie. a 20 metre layer. If the absorption characterics of SWIR was different such taht 80% of it was fully absorbed within just 4 microns (I have upscaled it to bring it in line with DWLWIR – K&T energy budget cartoon suggests DWLWIR is approximately twice that of Solar IR), the oceans would have boiled away long ago.
The issue is why if DWLWIR is heating the oceans, it does not lead to rapid and copious evaporation of the ocean? Potentially, there is so much energy being absored within the first 4 microns that it would give rise to about 14 to 18 metres of rainfall annually (which of course we do not have). So this raises the question whether the DWLWIR absorbed within the first 4 micron layer can be dissipated to depth before it would cause rapid and copious evaporation. It cannot be dissipated to depth by conduction since the first 4 microns is coller than the first few millimetres of the oceans. The temperature flux profile is upwards and hence energy absorbed in the first 4 microns cannot ‘swim ‘ against that ‘tide.’ The only other process suggested is ocean overturning. Willis in one of his comments explains this diurnal event. It is a slow mechanical process which could not dissipate energy faster than the rate of absorption of DWLWIR fuelling evaporation.
There are fundamental difficulties with the interaction iof DWLWIR and the oceans. The fact that we do not see copious amounts of evaporation provides some suppport for the view that DWLWIR does not effectively heat the oceans. Konrad’s expiriment suggest that it does not. I do not challenege his expiriment, but additionally postulate that there are other processes involved in the real world conditions encountered by planet Earth that may mean that not all the DWLWIR actually finds its way into the ocean, but instead much of it remains in the atmosphere above the oceans, never entering them.
Why is this relevant? well realy as to whether one accpets the gross energy flow budget, or the net energy flow budeget at the one that best describes real world conditions encountered on planet Earth.
.

Greg Goodman
June 8, 2014 3:54 am

KDK “Thus a practical guarantee the comments will be infested by Goodman holding court, trying to impress with his madz math skillz, seeing how many he can direct to his site to be flabbergasted by the blabbergasting”
I’m not trying to redirect anyone anywhere, I use my climategrog site as pastebin because this site does not let commenters insert graphics. I used to use tinypic until they put so much crap in the way, so I starteda WordPress site where it is at least clean and legible. This also means I can add a description of how plots are derived and what the data is.
Since I seem to be almost the only one apart from Willis actually prepared to do anything other than talk and handwave, that may appear “superior” to some. Remind me of what you have ever contributed to scientific analysis here.

Greg Goodman
June 8, 2014 4:16 am

Proof does not exist? I have been running these experiments since 2011 –
http://i47.tinypic.com/694203.jpg
I am not lying to you. I am not a climastrologist. I work in engineering.
Just conduct the experiment as shown. Remember –
“Tell me I’ll forget. Show me I’ll understand. Let me do it I will KNOW.”
Type is cheap. Do the experiments and you will know. I have little interest in just publishing my results. I am more interested in others replicating experiments.
=====
If you work in engineering, you know that your jpg diagram of two black boxes in no way represents “proof” , so why is that all you posted? It’s nonsense.
You equally know that comments like ” I can assure you” or “I am not a climastrologist” carry ZERO weight either.
Since no one else seems to have done this and you “have little interest” in publishing any results you may ( or may not ) have, that leaves us where were with NO proof. So your earlier claim that there is proof is unfounded. I did not call that lying, That is your choice of words.
If you have something lets see it. If you don’t, stop posting false claims that proof exists when it does not.
My impression (which could obviously be mistaken) is that you failed to get any credible results or never even got as far as constructing the experiment. You hope that someone else will do the donkey work and “reproduce” what you failed to produce. You will presumably then claim credit for the “original” work that “proved” you can’t heat ventilated water with IR.
Now I’d be very happy if I am mistaken and you get motivated to publish if you have some credible results. Thus far, it’s getting a bit like Murray Salsby syndrome.

June 8, 2014 4:18 am

From Greg Goodman on June 8, 2014 at 3:54 am:

Since I seem to be almost the only one apart from Willis actually prepared to do anything other than talk and handwave, that may appear “superior” to some. Remind me of what you have ever contributed to scientific analysis here.

And that makes it official. If it ain’t Willis waxing nostalgic about atolls or fishing or building pergolas that are proofed against climate change, his work just ain’t worth reading anymore since Goodman might be there. If you don’t want to see manure excreting, stop looking at bungholes.

ralfellis
June 8, 2014 4:29 am

Steven Mosher says: June 8, 2014 at 12:24 am
Willis ….“However, I think at this point I’ve heard every conceivable excuse for not being able to find the 11-year signal …”
Mosher …… I think it highlights what one gets when one starts to look at data with no real “idea” of how the system works.
__________________________________
Willis, Mosher,
What boggles my mind, is why nobody has seriously looked into this before, as a part of all the Climate slush-funds that are sloshing their way around the world. Why has nobody fully analysed all the possibilities? And why is it left to an amateur to debunk the many absurd claims that have been made (no offense, Willis, but I don’t think you receive a stipend from an educational establishment for your endeavors).
Clearly there are cycles in the climate record, with the 60-odd year cycle being perhaps the most obvious. So why do we not know what the primary driver of that cycle is? And saying it is the PDO is not an answer, for what drives the PDO?
Personally I think this cycle has to be something other than a natural resonance that just ‘happens’. Something is driving it. I feel the Sun probably is a primary influence, but how? Surely, these are the questions that Mann et all should be investigating and answering, rather than just scaring everyone with absurd extrapolations of temperature and disasters. How can the IPCC say they understand the Earth’s climate out to the next 150 years, if they do not understand the rather obvious 60-year climate cycle?
And sorry, Willis, please don’t ask me to do the math first – I would not know a Fornier Transformation from a Ferret. But surely there is someone in the IPCC or in academia that does. Or, failing that, why not just pay Willis to look. Geeez, in terms of the amount of money wasted on climate ‘science’, giving Willis a stipend and an office would be a drop in the (warming or cooling) ocean.
Ralph

Genghis
June 8, 2014 4:31 am

Willis, the buoy’s don’t measure the surface temperature, the skin where the evaporation and radiation actually takes place. They measure the water temperature just under the surface which clearly shows the night vs day pattern, just as the air temperature above the surface does too.
Do you know of a source that actually measures the surface temperature? I can also confidently predict (postdict?) that if you match the wind speeds to your buoys temperature data that the wind speed dropped allowing the temperature to rise.
Also if the wind speed isn’t high enough the surface temperature will show the night vs day pattern, if it is clear skies. Pointing the IR gun skyward, the bottom of the darker clouds is generally in the 76˚ F range while the clear sky areas is around 34˚ F at night and in the 40˚ F range during the day. (I use Fahrenheit because it is a finer scale, whether it is more accurate or not is another thing)
I am extremely familiar with the buoy data, as well as all of the weather forecast models, Chris Parker, satellite data, etc. etc. As the Admiral gets very upset if the sailing conditions are not to her liking and my number one goal in life is to keep the Admiral happy.

Greg Goodman
June 8, 2014 4:32 am

Willis: “In any case, what I’m looking for is not a study. It is a dataset and a corresponding procedure for extracting the 11-year cycle. ”
Since we are all agreed that the “solar cycle” is it not a single fixed period no one is going to be able to extract such thing even if there is a solar signal to be found. It has to be linked directly to some proxy of solar “activity”.
You chose cross-correlation to examine that, which seems a very sensible first step. Unfortunately you seem to have chosen annual averages. one thing for which Shaviv2008 could be criticised for. That appears to degrade the signal to a level you regard as non existent.
When I do the same thing with monthly data and find what your own criteria suggest should be significant, you steadfastly ignore the result and discuss anything else instead.
http://climategrog.wordpress.com/?attachment_id=959
Strange.

Greg Goodman
June 8, 2014 4:40 am

Greg says: ” Remind me of what you have ever contributed to scientific analysis here.”
KDK replies:
http://wattsupwiththat.com/2014/06/06/sunspots-and-sea-surface-temperature/#comment-1657029
Hmm, just as I thought: nothing. Just wanted to check. Thanks for the confirmation.

June 8, 2014 5:08 am

@ Greg Goodman on June 8, 2014 at 4:40 am:
It’s okay, Greg. I forgive you.

ralfellis
June 8, 2014 5:10 am

P.S.
As a matter of interest, Willis, will your many analyses of the data show up a variable cycle, like the Sunspot Cycle – which appears to vary between 10 and 14 years? Does a FT of the raw SSN data, for example, show a prominent peak at 11 or so years?
So can we easily detect variable cycle-lengths in the temperature record? Is this why longer cycle lengths are more prominent in the temperature data, because the shorter cycle lengths are variable and jumbled? Is the 60-year PDO climate cycle a culmination of many variable smaller cycles of about 12 years in duration?
And please don’t ask me for the math. As mentioned previously, I would not know a Fornier Transformation from a Ferret. But I am interested in the results.
Ralph

Donald Morton
June 8, 2014 5:22 am

Willy
I have followed with interest your efforts to detect the 11-year solar cycle in meteorological data and the lack of evidence for any correlation. So I am wondering whether longer-term variations in solar activity have had any effect. The 14C and 10Be radioactive isotopes provide good proxies for solar activity. Their anticorrelation with the historic temperature swings of the Little Ice Age and the Medieval Warm Period may not be long enough for any solid conclusion. However, Bond et al 2001, Science 294, 2130 found good correlation over 12 000 years in cores of layered ocean sediments. In another example Neff et al 2001 Nature, 411, 290 found excellent correlation of 14C with the delta18O proxy for monsoon rainfall in a stalagmite from a cave in Oman from 6200 to 9600 years ago. I would welcome your views on such studies. Even though we do not know the mechanism, how good is the evidence for a solar contibution to climate change?

June 8, 2014 6:16 am

From ralfellis on June 8, 2014 at 5:10 am:

Does a FT of the raw SSN data, for example, show a prominent peak at 11 or so years?

WoodForTrees has the SIDC SSN info:
http://woodfortrees.org/plot/sidc-ssn/from:1750/to:2014
It can do a FT for you. Check the Help link for commands and tips.
http://woodfortrees.org/plot/sidc-ssn/from:1750/to:2014/fourier/from:1/to:50/magnitude
Over the record, it’s doing a FT, limited from 1 year up to 50 years. “Magnitude” is something done because that particular FT method uses complex numbers (they have real and imaginary components), there are others that don’t. “Magnitude” joins the imaginary portion with the real part so the info isn’t lost because the imaginaries aren’t being displayed.
9 and 12 years are stronger than 11 years over the full record. The 24 years makes sense because the poles flip during the 11+ year cycle, so it takes 22++ years for the full Hale cycle.

So can we easily detect variable cycle-lengths in the temperature record?

You now have a tool you can play with, with the datasets it has access to. Go forth and explore.

June 8, 2014 6:22 am

I read that some indigenous peoples of Alaska are losing their traditional fishing grounds because of AGW driven permafrost melting causing the shoreline to subside into the ocean.
I pulled up a satellite image of an unrelated coastline, determined from the well-accepted Beysian/Confusium correlation applied to beach gravel distributions that 1,256,342 years ago the average tidal fluctuation was 3.25 mm per parsec less than today. And, no, I did not forget to regress the dilithium cross-compounded monolith by the well established factor of wtf^2+(hoo-nos). Sheesh, anybody who knows anything knows how to do that.
Applying statistical slicing, dicing and leveling it appears highly likely that a large scrap tire dump outside Podunk, OK is the only possible source of this frightening threat to humanity and the only way to mitigate this end to life as we know it is to redistribute these tires via drone to each & every household using gender neutral genetic marker addresses.
My data, software, and methods are in a sealed and booby trapped canister at location 75.225 degrees W, 0.000 degrees N. Prove me wrong, I dare you, otherwise my work is unimpeachable.

Greg Goodman
June 8, 2014 6:51 am

“to each & every household using gender neutral genetic marker addresses.”
What about those with trans-gender addresses?! Sorry not P.C. : recommend rejection.

ralfellis
June 8, 2014 7:16 am

(((So can we easily detect variable cycle-lengths in the temperature record?)))
You now have a tool you can play with, with the datasets it has access to. Go forth and explore.
___________________________________
Thanks, Kakada, that is most interesting. But I think I will need a Willy to explain what it means.
http://woodfortrees.org/plot/sidc-ssn/from:1750/to:2014/fourier/from:1/to:50/magnitude
From what I see, the 11 year sunspot cycle is missing in this Fourier Transformation of SSNs, while the double cycle is very prominent. And this is despite the approx 11 year cycle being the most prominent when visually looking at a SSN graph. And yet the triple or quadruple cycle is missing from the Fourier. Why does a double cycle display, but not the single, triple or quadruple?
So could the sunspot cycle be visible in the climate record as a quintuple (60-year) resonant or heterodyning multiple of the smaller (approx 12-year) sunspot cycle??
Ralph

Greg Goodman
June 8, 2014 7:38 am

Ralph “From what I see, the 11 year sunspot cycle is missing in this Fourier Transformation of SSNs, while the double cycle is very prominent.”
Sorry Ralph but WTF.org is a crock for anything more than fitting inappropriate linear trends to non-linear data and distorting it with crappy running means. It is totally inappropriate to offer FT as a click-go-tool like that. Also it is so badly present that I, having done plenty, can’t relate to the crap way the result is plotted.
FT does require quite a bit of understanding before you can make any sense of what it does. It’s well worth looking into but splashing about on WTF.org will be totally fruitless and frustrating. Don’t even try.
Willis’ “slow FT” code is available to play with and is probably more intuitive that a true FT. Look at this recent threads for code, examples and ample discussion by lots of people with varying degrees of knowledge of the subject.
You will also find answers to some of the questions you asked above, SSN contains three close frequencies around 11 years plus circa 22y. This is why it is a shape-shifter. You will find lots of detail on that.
No point in repeating the highlights here, suggest you go and read the threads. As always, more chaff than wheat so take coffee and biscuits with you. 😉

Greg Goodman
June 8, 2014 7:47 am

“Is the 60-year PDO climate cycle a culmination of many variable smaller cycles of about 12 years in duration?”
IMO, it is likely that the various long period climate “oscillations” are the result of interactions of lunar and solar influences with periods around 9y and 10-11y respectively. But climate is complex and the last 30y have largely been wasted attempting to prove a foregone conclusion to the exclusion of all else.
Perhaps in another ten years a better understanding of climate as more than a single variable problem will have emerged.

Pamela Gray
June 8, 2014 8:30 am

Once again I must be failing terribly at what WAS, I thought, the scientific method. First observe. If it cannot be observed it is likely to be such a small affect it can safely be ignored. That is the case with TSI. It does indeed have the potential to cause a cyclic change in temperature and can be mathematically calculated. But it can be readily overcome by much more powerful intrinsic variability, thus can be safely ignored, buried as it is in noise. Many here on either side of the solar debate advocate that position: ignore TSI and yes Earth has powerful intrinsic-driven variability (and think so correctly IMO). Yet, readily ignoring a mechanized plausible mathematically defensible solar related addition to Earth’s temperature while admitting to powerful intrinsic variability does not seem to inform them about ignoring other far less powerful solar parameters. The logic escapes me that a small little mutt can be ignored but lets focus in on the hair on a flea’s ass. Even more, let’s focus in on that after we have split it in two and statistically curled it.

June 8, 2014 8:38 am

From ralfellis on June 8, 2014 at 7:16 am:

Why does a double cycle display, but not the single, triple or quadruple?

Because the “11 year cycle” is only a half cycle. At the bottom of an 11-yr portion, the magnetic poles flip, which is actually a drawn-out thing where they might not flip simultaneously. The Sun is a messy place.
The Sun has to pass through the bottom of another 11-yr portion for the magnetic poles to return to the previous orientation.
So what you see are Hale cycles, the flipping and the return together, which shows up as a 24-yr cycle.
The “triple” would be three half-cycles. The “quadruple” would only be the second harmonic (Frequency * 2) of the Hale cycle. So neither should show up much. Although given the variations in the “11 year” length, a “triple” could be anywhere from 28 to 36 years long.
Of course, things change when you throw away some data. I’m going to start at 1880, when the GISTEMP dataset starts, and throw away the first 130 years, half the data.
http://woodfortrees.org/plot/sidc-ssn/from:1880/to:2014/fourier/from:1/to:50/magnitude
Now we’re down to only five full Hale cycles, using the 24-yr amount. Before we might have had eleven, or ten. The 24-yr high peak is gone. But there are many iterations of the “11 year cycle” remaining, shown peaking at 13 but still strong at 12 and 11 years.

So could the sunspot cycle be visible in the climate record as a quintuple (60-year) resonant or heterodyning multiple of the smaller (approx 12-year) sunspot cycle??

Let’s look. We’ll do a FT of GISTEMP too. I’m using the “normalise” function to rescale both the same for easy comparison, usable as we’re just matching peaks.
Also with only 134 years of data, looking for a 60 year cycle is a stretch, I’ll bump it out up to only 65 years.
http://woodfortrees.org/plot/sidc-ssn/from:1880/to:2014/fourier/from:1/to:65/magnitude/normalise/plot/gistemp/from:1880/to:2014/fourier/from:1/to:65/magnitude/normalise
Where is that “60 year” cycle? Can you really claim there is anything between the two that really matches up, except perhaps the Hale cycle at 24 years, which might be spurious in the temperature data?

June 8, 2014 8:53 am

Whoops. Re previous comment, “second harmonic” was in error, that’s not frequency*2, not an overtone. Although the link is still informative reading. It’d actually be the 1/2 subharmonic, frequency divided by 2.
But you get the idea. What happens every 24 years may look like it happens every 48 years, or 72 years, etc.

mobihci
June 8, 2014 9:00 am

mosher thinking-
“The solar variation is so minor that I do the following thought experiment.
I make a chart of TSI versus time.
I label it c02.
I make a chart of temperature versus time
I label it temperature.
Then I imagine what a skeptic would say If I claimed that chart one helped to explain chart two.”
make it about something else, then ignore the obvious things like … ohh, just about every proxy we have that says co2 lags temps, NOT the other way around AND temps move with sunspot numbers through Be records. hmm, it takes skill to ignore so much.
this thread is a fine example of that skill in action. willis congrats mosher for thinking like him, which says it all really.
it is obvious that the goal of this thread is not to determine whether there is an eleven year cycle evident in the record, it is just to belittle those looking for it. it really is not a simple task. there are just so many possibilies there. to claim that one knows without doubt that it should be most visible in the the 11 year cycle is a clear failure and outright arrogance. it is this form of arrogance that we see every day in the climate science community. it is unexpected from the engineering community, which i thought willis was from.
did willis die recently and mosher take over his account?!

Pamela Gray
June 8, 2014 9:19 am

Crispin in Waterloo
June 8, 2014 9:19 am

“We hold similar views, and recall that we engaged in much discussion on this on Willis’ article on ‘Radiating the Oceans’ (which i personally consider to be not one of Willis’ stronger articles – sorry willis, just my personal opinion). However, the point that the warmists would raise is that if DWLWIR heats the atmosphere, even if it does not heat the ocean below, then due to the warmer atmosphere above the ocean,the heat loss from the ocean is lower/slower, thereby helping to maintain or even produce higher ocean temperatures over time.”
Just complimenting you guys along with Greg on some good insights and cogent explanations. I did want to point out that the mention of spray and spume and the generally wet conditions above the ocean are only part of the LWIR absorption. Water vapour itself didn’t get a direct mention.
Something else worth mentioning is that ocean water is quite reflective as well as having a high emissivity. I do not believe the story about water having an E of 0.7 – I have measured too much water with an IR thermometer to accept such a low number. The emissivity of water is in the high ‘9’s’. A common mistake would be to measure the water’s bulk temperature and interpret that as being the same as the surface skin temperature. It is about the same as black oil which is also quite reflective though they react differently to the angle of incidence.
The big influence is of course the water vapour near the ocean. I don’t think much LW gets to the surface. What leaves bounces back and forth a lot too of course, so overall the vapour is an insulating blanket. CO2 is simply a bit player there is so little of it.
A friend sent me a message the other day saying that the volume of water condensed from vapour created per annum by burning fossil fuels is about the same as the volume of Lake Simcoe in Ontario. That’s a lot of GHG but also a lot of condensing heat transport medium. The thunderstorm thermostat hypothesis rules, OK?

Ulric Lyons
June 8, 2014 10:52 am

“Where is the climate dataset that shows the ~11-year sunspot/magnetism/cosmic rays/solar wind cycle?”
The solar wind is not in a well defined ~11 cycle: http://snag.gy/hSqT4.jpg

Bart
June 8, 2014 11:11 am

Greg Goodman says:
June 8, 2014 at 7:47 am
“IMO, it is likely that the various long period climate “oscillations” are the result of interactions of lunar and solar influences with periods around 9y and 10-11y respectively.”
I agree. I do not see a peak in the SST PSD specifically associated with 11 years, but there are several peaks at harmonics corresponding to such interactions, and in measure of what might be expected if they modulate one another.
I don’t want to get mired again in non-productive dialog with Willis. But, I did happen upon this entry in Wikipedia which may be of interest to him. Perhaps it has already been pointed out to him, and I’ll probably get blasted for some sort of imagined deviousness in providing it. For the record, I’m not trying to make any point at all, just trying to be helpful, as always.

Ulric Lyons
June 8, 2014 11:27 am

“As a result, there is no “un-even solar heating of the polar regions due to the distance from the Sun”.It doesn’t exist.”
Annually no, but seasonally there is.

Greg Goodman
June 8, 2014 12:55 pm

Willis, if you reply to on phrase in a comment, I am assuming telepathic powers by assuming you read to following line as well.
Greg Goodman says:
June 7, 2014 at 12:56 pm
“So smart I’d done it and posted it 9 hours before you told me “directly” to get off my butt and do it.
I’ll take that as an almost apology 😉
Without worrying about the FT of CC for the moment. What information do you think can be derived from cross-correlation. You used it to support your impression that there is no solar signal, so you must expect that something could be there that was not. ”
===
But I digress. Let’s continue the search for the illusive solar signal.
I used the full hadISST monthly data from the link shown in the graph. The SSN data was cropped to the same starting date (1870). The cross-correlation is the cross-correlation of the full overlap available at each lag ( as I’ve pointed out before a flat line is not valid, it should curve up as lag shortens the data. That’s not really an issue here though, it won’t vary noticeably in the central portion.)
W: “What your cited graph actually looks like, however, is that you forgot to detrend your datasets before doing the cross-correlation …”
The slope affects the correlation. If you want to know where the max correlation happens and what it’s value is, why would I want to distort both datasets by removing a spurious linear trend from both before doing CC?

Editor
June 8, 2014 3:35 pm

Willis – Thanks for your reply to my last comment. I do accept that you have looked very diligently (and skilfully) at just about everything you can think of, and that the signal has not been there. I also accept that given your extensive efforts and others’ the probability of the signal existing is (to put it very conservatively!) small. Many thanks for trying, and many thanks for posting it all here. It’s part of what makes WUWT such an interesting and informative blog. [Thinks : if something that could be helpful to sceptics is demolished on a warmist site, there’s always the suspicion of bias. On WUWT it’s credible.]
Steven Mosher – I find your sneering comments illogical unjustified unworthy and unbecoming. Willis is looking for something, and he can’t find it, so others make suggestions as to where else he could look. So they are being helpful. Willis has looked in all the suggested places, and the thing he’s looking for isn’t in any of those places either. In all of that process, no-one has necessarily had any belief about whether the thing existed or not, an open mind is all that was needed. You are the one with the closed mind that is out of order.
I still think that Willis’ “Regular cycles which are apparently real appear, last for a half century or even a century, and then disappear for a century …” could be relevant. Does it necessarily mean that all such cycles are, in terms of what causes them, an illusion, or does it mean that when conditions change then effects change too? Even if effects disappear at times, wouldn’t they still be visible when averaged over the full record? The reality is that (a) I have to wait for someone to find the answer, or (b) Willis has found the answer (it’s an illusion), or (c) I have to find it myself. The last option, regrettably, is very unlikely.

June 8, 2014 3:49 pm

Greg Goodman says:
June 8, 2014 at 4:16 am
——————————–
“My impression (which could obviously be mistaken) is that you failed to get any credible results or never even got as far as constructing the experiment.”
Greg, steady on. You are mistaken. I believe you may have mis-interpreted my comment about publishing results. I showed you not just a jpg of the revised experiment design, but a photograph of the very first of these experiments I built. This involved reflecting IR back to the surface of warm water. Results were published at Talkshop. My point about publishing results is this – one persons results carry far less weight than other persons replicating experiments.
I was not asking you to do the donkey work and run an experiment I had not run myself. Rather when you asked for proof, I gave you what I believed was the best proof possible, instruction on how to replicate the experiment.
I struggle to think of any more solid proof than an experiment you can replicate for yourself.
If you build the initial version of the experiment with IR reflected back to one cooling sample you will achieve ~1.5C divergence in ~30min in the evaporation constrained run. If you use a constant strong IR source as shown in the second version you will achieve over 5C of divergence. But I am not asking you to take my word for it. I am showing you how to check for yourself, just like Genghis is doing with IR thermometers and SST.

RH
June 8, 2014 3:57 pm

Here is a comparison of the of Hadcrut3 and sun spot numbers from 1950 through 2014. There is a distinct 11 year cycle evident with both. spectrum
I used data from woodfortrees.org and analyzed it with Audacity.
The 11 year cycle is less evident when including older data. Maybe the older the data the more crap it is.

June 8, 2014 4:10 pm

Crispin in Waterloo says:
June 8, 2014 at 9:19 am
———————————–
“Something else worth mentioning is that ocean water is quite reflective as well as having a high emissivity. I do not believe the story about water having an E of 0.7 – I have measured too much water with an IR thermometer to accept such a low number. The emissivity of water is in the high ’9′s’.”
This is getting a bit off topic, but I have been conducting some recent experiments into this issue. These involve measuring water surface temp with an IR thermometer under a cryo cooled “sky”. I can only get down to -40C at this stage. But with background IR minimised I need to adjust emissivity down to below 0.8 to get a reading matching surface thermocouple. An emissivity setting of 0.95 is fine for environmental measurement of water, but if that figure were used for calculating the radiative cooling rate of the oceans in the absence of atmosphere….

Pamela Gray
June 8, 2014 4:50 pm

Calculating for significance is as fraught with misguided creativity as calculating for linear trend lines. Trouble is, those who fail to understand the underlying math and proofs of data analysis think they can come up with a facsimile and call it good.
One of my favorites is a linear trend line through noisy data that was calculated by subtracting the first data point from the last data point and dividing by number of weeks between them to come up with the linear trend function. And then based on that result, use the function to substantially determine whether or not a student has a learning disability. When I protested, and stubbornly insisted that they should use linear calculations that were valid and reliable for noisy data instead of the made up of whole cloth calculation, I was threatened with a one day suspension.
Please folks, in this challenge by Willis to come up with something, don’t play around with statistical significance. Be conservative and use the gold standards.

Greg Goodman
June 8, 2014 5:30 pm

RH says:
Here is a comparison of the of Hadcrut3 and sun spot numbers from 1950 through 2014. There is a distinct 11 year cycle evident with both. spectrum
I used data from woodfortrees.org and analyzed it with Audacity.
The 11 year cycle is less evident when including older data. Maybe the older the data the more crap it is.
====
I note in your “spectrum” link they both show 5.5y too. That is part of what makes up the shape of the solar cycle which rises quickly then tails off.
The late 20th c. period is one where it “works” which is why the question of cherry-picking arises. As you note earlier it works less well. It may have something to do with sampling biases in earlier data or just as likely the speculative “corrections” that are done to the data, mainly I think it is that the SST record quite a mix of cycles:
There is a fairly strong circa 9y component in most ocean basins. As this drifts in and out of phase with 11y cycles, as time progresses it will either add to or disrupt the 11y signal. This artificially increases it in much of the latter part of 20th c. and pretty much destroys it or pushes it out of phase in pre WWII period. Add to this that the “11y cycle” is a triplet of three close frequencies also interacting with each other and changing the profile and height of the solar peaks themselves plus a smaller 22y component.
As far as I have been able to tell, the 9y signal is similar to but a bit larger than the solar signal. About half of what appears to be solar correlation when it “works” is in-phase contribution of 9y.
The “9y” cycle seems more stable than the complex solar signal, it appears to be 9.05 to 9.1y , with various authors giving various margins of uncertainty, I suspect it is quite close to that central value.
All this means that tracking down any match to the solar signal is not going to just jump out of the page as some seem to expect it will. “It’s the sun stupid” is well, stupid.
IPCC seem to favour 0.1K pk-pk variation in surface temps over the 11 year cycle. It may be a fair bit stronger but that is order of magnitude concerned. We are looking for that against a record with annual swings about two orders larger with opposing phases in asymmetric hemispherical variations and 6mo tropical seasons. Plus all the rest of the churning climate system.
Significance levels judges against naively simplistic “red noise” models are of little relevance.
The school of AGW says it’s GHG+stochastic , in that ‘one variable’ model and under the assumption the rest is chaotic, the red noise test makes sense. Under a model that anticipates solar, lunuar, anthro and other ( possibly driven ) factors + noise , the individual components will be small and will not be “significant” against a simplistic statistical model where everything else is red.
Neither is unconstrained red noise a suitable model for variation in variables that are not free to do a ‘drunkards walk’ across the park but are instead bounded by negative feedbacks to remain on the path.
I think all that answers some of Mike Jonas’ points too.

Greg Goodman
June 8, 2014 5:52 pm

W: “As I have said many times, the fact that the solar cycle is irregular does not prevent us from detecting it in the sun, using any one of a number of methods. ”
Agreed, my point was that is it not a simple fixed 11 years.
W: “As a result, the claim that the effect of the cycle is magically undetectable in climate datasets for unknown reasons won’t fly.”
Is that supposed to relate to my quote? I did not say it was, I said it has be sought as directly to the solar signal , because of its irregular nature.
How are you getting on with interpreting the 0.25 correlation coefficients? What does your ‘program’ give for circa 1700 data points?
If you are having trouble with my cross-correlation, do your own with the full monthly data, without averaging, “binning”, detrending, just a straight CC. Correlation is simply and uniquely defined and calculable at each lag value.
Do you still think it is necessary to detrend before doing CC ? That would seem to be an error to me in the context of assessing magnitude and timing of peak CC.

aaron
June 8, 2014 5:58 pm

w., I don’t remember, did you look at CERES SW outgoing radiation and solar activity/cycle?
Also, I would expect that ocean circulation patterns would dominate the SST and that increased SW in the ocean may very localized. Perhaps it would be good to look at solar activity between el Nino events.

Greg Goodman
June 8, 2014 6:04 pm

Konrad: “Results were published at Talkshop. My point about publishing results is this – one persons results carry far less weight than other persons replicating experiments. ”
I first came across your name on TS, I recall similar vaporous claims with no numbers. If the “proof” is over there, I must have missed it, please link. So far there’s nothing to “replicate”. One person’s _results_ have far more weight than one person’s ” I can assure you”.